This document evaluates the performance of mean and median filters for reducing speckle noise in synthetic aperture radar (SAR) images off the coast of the Gulf of Guinea. The mean filter performs better for noise levels below 10% while the median filter performs better for higher noise levels, as measured by mean squared error and peak signal-to-noise ratio. Designing an adaptive filter that switches between mean and median filtering depending on the noise level could provide the best reduction of speckle noise in SAR images.
Remote sensing involves collecting information about objects or areas from a distance without making direct contact. It works by sensing and recording reflected or emitted energy and processing, analyzing data. Key points are that it obtains data through passive sensors that sense sunlight reflected by Earth or active sensors like radar that emit and sense their own radiation. Platforms can be ground, airborne or spaceborne. Spaceborne platforms are in either geostationary or polar orbits. [/SUMMARY]
Iirs lecure notes for Remote sensing –An Overview of Decision MakerTushar Dholakia
The document provides an overview of remote sensing including:
1) Defining remote sensing as acquiring information about Earth's surface without physical contact using sensors to detect reflected or emitted energy.
2) Describing the basic components and processes of remote sensing including emission, transmission, interaction with the surface, and sensor data acquisition.
3) Detailing the interaction of electromagnetic radiation with Earth's surfaces and the information that can be derived from changes in magnitude, direction, wavelength and other properties.
4) Explaining the different types of remote sensing platforms, sensors, resolutions and wavelengths used in remote sensing from visible light to microwaves.
5) Providing an overview of Indian remote sensing satellites
physics of remote sensing,ideal remote sensing,swath,platform,sensor,orbit and its characteristics,electromagnetic radiations,EMR solar radiations and its application,shortwave and long waves,spectrul reflectance curve, resolution AND multi concept,FCC,
PHOTOMETRIC ANALYSIS OF THE OCTOBER 2010 HAZE EVENT OVER SINGAPORE.pdfgrssieee
This document analyzes a haze event over Singapore in October 2010 caused by smoke from fires in Sumatra, Indonesia. Photometric and LIDAR data were used to characterize the aerosols. Analysis showed high concentrations of fine particles less than 0.4 microns from the fires, with air quality degraded and visibility reduced. Trajectory and inversion modeling indicated both fresh and aged smoke was transported to Singapore from the Sumatra fires.
This document discusses the application of remote sensing and geographical information systems in civil engineering. It begins by defining remote sensing as the acquisition of information about an object without physical contact, typically by measuring electromagnetic radiation. It then defines geographical information systems as a system for capturing, storing, analyzing and presenting spatially referenced data. The document provides examples of how remote sensing data from sources like Google Earth can be spatially analyzed using a GIS. It proceeds to discuss key concepts in remote sensing including the electromagnetic spectrum, atmospheric interactions with radiation, and radiation measurement principles.
Hyperspectral remote sensing of vegetationSakthivel R
This document discusses the use of hyperspectral remote sensing to study vegetation. Hyperspectral data consists of hundreds or thousands of narrow wavebands along the electromagnetic spectrum, providing more detailed information than broadband data. Hyperspectral sensing is used to characterize vegetation types and properties like biomass, biochemical compositions, diseases, nutrients, and moisture. Spectral reflectance spectra can show characteristic absorption features related to plant constituents for live and dry vegetation. Hyperspectral vegetation indices and multi-band indices are developed to analyze vegetation characteristics while eliminating redundant data bands. Classification methods like regression, clustering, and neural networks are applied to hyperspectral data for analyzing and mapping different vegetation classes.
This document provides an introduction to satellite remote sensing. It discusses key topics such as the definition of remote sensing, the stages of remote sensing including energy sources, sensors, and data interpretation. It also covers different types of remote sensing based on platform, orbital characteristics, energy sources, components, and spectral characteristics. Different sensors, image resolution, electromagnetic radiation properties, and interactions with the atmosphere and earth surface are described. The history and development of remote sensing techniques are briefly mentioned. In summary, the document provides a comprehensive overview of the fundamental concepts and components of remote sensing from multiple perspectives.
Remote sensing involves obtaining information about objects through non-contact sensors rather than physical contact. It has a long history dating back to aerial photography in the 1800s. Remote sensing works by detecting electromagnetic radiation reflected or emitted from objects. Different objects reflect different amounts of radiation depending on their material properties and the wavelength observed. Key components of remote sensing systems include an energy source, sensors to record radiation, and processing of the recorded data. Remote sensing has many applications in fields like geology, agriculture, forestry, and military/security. It provides a useful tool for mapping and monitoring Earth's surface and atmosphere.
Remote sensing involves collecting information about objects or areas from a distance without making direct contact. It works by sensing and recording reflected or emitted energy and processing, analyzing data. Key points are that it obtains data through passive sensors that sense sunlight reflected by Earth or active sensors like radar that emit and sense their own radiation. Platforms can be ground, airborne or spaceborne. Spaceborne platforms are in either geostationary or polar orbits. [/SUMMARY]
Iirs lecure notes for Remote sensing –An Overview of Decision MakerTushar Dholakia
The document provides an overview of remote sensing including:
1) Defining remote sensing as acquiring information about Earth's surface without physical contact using sensors to detect reflected or emitted energy.
2) Describing the basic components and processes of remote sensing including emission, transmission, interaction with the surface, and sensor data acquisition.
3) Detailing the interaction of electromagnetic radiation with Earth's surfaces and the information that can be derived from changes in magnitude, direction, wavelength and other properties.
4) Explaining the different types of remote sensing platforms, sensors, resolutions and wavelengths used in remote sensing from visible light to microwaves.
5) Providing an overview of Indian remote sensing satellites
physics of remote sensing,ideal remote sensing,swath,platform,sensor,orbit and its characteristics,electromagnetic radiations,EMR solar radiations and its application,shortwave and long waves,spectrul reflectance curve, resolution AND multi concept,FCC,
PHOTOMETRIC ANALYSIS OF THE OCTOBER 2010 HAZE EVENT OVER SINGAPORE.pdfgrssieee
This document analyzes a haze event over Singapore in October 2010 caused by smoke from fires in Sumatra, Indonesia. Photometric and LIDAR data were used to characterize the aerosols. Analysis showed high concentrations of fine particles less than 0.4 microns from the fires, with air quality degraded and visibility reduced. Trajectory and inversion modeling indicated both fresh and aged smoke was transported to Singapore from the Sumatra fires.
This document discusses the application of remote sensing and geographical information systems in civil engineering. It begins by defining remote sensing as the acquisition of information about an object without physical contact, typically by measuring electromagnetic radiation. It then defines geographical information systems as a system for capturing, storing, analyzing and presenting spatially referenced data. The document provides examples of how remote sensing data from sources like Google Earth can be spatially analyzed using a GIS. It proceeds to discuss key concepts in remote sensing including the electromagnetic spectrum, atmospheric interactions with radiation, and radiation measurement principles.
Hyperspectral remote sensing of vegetationSakthivel R
This document discusses the use of hyperspectral remote sensing to study vegetation. Hyperspectral data consists of hundreds or thousands of narrow wavebands along the electromagnetic spectrum, providing more detailed information than broadband data. Hyperspectral sensing is used to characterize vegetation types and properties like biomass, biochemical compositions, diseases, nutrients, and moisture. Spectral reflectance spectra can show characteristic absorption features related to plant constituents for live and dry vegetation. Hyperspectral vegetation indices and multi-band indices are developed to analyze vegetation characteristics while eliminating redundant data bands. Classification methods like regression, clustering, and neural networks are applied to hyperspectral data for analyzing and mapping different vegetation classes.
This document provides an introduction to satellite remote sensing. It discusses key topics such as the definition of remote sensing, the stages of remote sensing including energy sources, sensors, and data interpretation. It also covers different types of remote sensing based on platform, orbital characteristics, energy sources, components, and spectral characteristics. Different sensors, image resolution, electromagnetic radiation properties, and interactions with the atmosphere and earth surface are described. The history and development of remote sensing techniques are briefly mentioned. In summary, the document provides a comprehensive overview of the fundamental concepts and components of remote sensing from multiple perspectives.
Remote sensing involves obtaining information about objects through non-contact sensors rather than physical contact. It has a long history dating back to aerial photography in the 1800s. Remote sensing works by detecting electromagnetic radiation reflected or emitted from objects. Different objects reflect different amounts of radiation depending on their material properties and the wavelength observed. Key components of remote sensing systems include an energy source, sensors to record radiation, and processing of the recorded data. Remote sensing has many applications in fields like geology, agriculture, forestry, and military/security. It provides a useful tool for mapping and monitoring Earth's surface and atmosphere.
Meteorological Technology International, Jan 2010laurajairam
This document discusses advances in satellite sensor technology that enable more accurate climate monitoring from space. Specifically:
1. Prior satellite sensors had limitations like coarse spectral resolution and degrading calibration over time, making it difficult to establish long-term climate trends from space data.
2. New technologies can achieve much greater measurement accuracy, stability over decades, fine spectral resolution, and precise knowledge of spectral response needed for undisputed climate monitoring.
3. Advances like onboard high-accuracy blackbody calibration sources and hyperspectral imaging bring National Institute of Standards and Technology calibration capabilities to satellites. This eliminates prior limitations and allows climate trends to be reliably measured from space.
Errors in GPS positioning come from several sources, including ephemeris data that is up to two hours old, clock errors in satellite atomic clocks, and delays caused by signals passing through the ionosphere and troposphere. Additional errors stem from multipath interference from reflected signals, selective availability that was used by the US military, and geometry of satellite positions relative to the receiver. Most of these errors can be corrected through algorithms in the receiver but some may still cause inaccuracies of a few meters.
Remote Sensing - A tool of plant disease managementAnand Choudhary
The document provides an overview of remote sensing in plant pathology. It discusses the history and fundamentals of remote sensing, including different types of platforms, resolutions, and the objectives and case studies of remote sensing in plant disease management. Key objectives of remote sensing in plant pathology include assessing diseases over large areas, understanding disease-environment relationships, detecting and identifying plant diseases, and aiding disease management. Case studies demonstrate uses of remote sensing for various crop diseases.
This document provides an introduction to the fundamentals of remote sensing. It discusses that remote sensing involves acquiring information about the Earth's surface without direct contact, using sensors to detect reflected or emitted energy. It describes the seven elements of the remote sensing process, including an energy source, interactions with the atmosphere and target, sensor recording, data transmission and processing, interpretation, and application of results. It also discusses electromagnetic radiation, the electromagnetic spectrum, and how radiation interacts with and is scattered or absorbed by particles in the atmosphere.
This document discusses remote sensing. It defines remote sensing as acquiring information about objects without direct contact, using electromagnetic radiation. It describes how remote sensing uses platforms like aircraft and satellites to collect passive and active sensor data. It provides examples of different sensor types, including photography, infrared, LIDAR, and multispectral scanning. It also discusses important remote sensing concepts like spatial, spectral, radiometric, and temporal resolution. Finally, it highlights how the SLOSH model uses remote sensing data to accurately predict hurricane storm surges and inundation areas.
Remote sensing uses sensors on satellites and aircraft to measure electromagnetic radiation from the Earth's surface. This data can be used to support fisheries and aquaculture management by providing information on sea surface temperature, ocean color, ocean salinity, land cover, and the location of coastal aquaculture structures over large geographic areas. A case study demonstrated how satellite images could map fish ponds and cages in a coastal region of the Philippines. Remote sensing will continue playing an important role in monitoring fisheries and aquaculture by providing global and repeated observations in a cost-effective manner.
This presentation consist of remote sensing, types of remote sensing and also about the radiometers systems. I have also discussed about the types of radiometers system and how it work. I have also discussed about the principle on which it works. Also I have discussed about the applications .
Remote sensing and application by Nikhil PakwanneNIKHIL PAKWANNE
Remote sensing is the process of obtaining information about objects or areas from a distance, without physical contact. It involves the use of electromagnetic radiation to detect and classify objects on Earth through aerial sensors or satellites. The key components of a remote sensing system include an energy source, a sensor to record electromagnetic radiation, transmission of data to a receiving station, and processing to extract information. Remote sensing provides advantages like rapid coverage of large areas, accessibility to remote or dangerous regions, and collection of geo-referenced digital data. Common applications of remote sensing include agriculture, geology, urban planning, hydrology, land use mapping, forestry, and ocean monitoring.
Remote sensing in plants, botany, application in vegetation classification and conservation, basic mechanism of remote sensing,how it works, satellite mapping techniques and aerial mapping
Remote sensing uses sensors on satellites or aircraft to detect objects on Earth without physical contact. It has various applications in coastal management like mapping watersheds and resources, identifying erosion-prone areas, and monitoring coastal zones for environmental impacts. The key advantages of remote sensing for coastal management are its ability to provide synoptic and repetitive views of large areas, including during bad weather. Important satellite sensors include Landsat, SPOT, IRS and RADARSAT, which can monitor coastal geomorphology, habitats, and locate offshore fishing grounds. Innovation in sensor technology is needed to better understand and manage threats to ocean ecosystems.
Propagation Effects for Radar&Comm SystemsJim Jenkins
This three-day course examines the atmospheric effects that influence the propagation characteristics of radar and communication signals at microwave and millimeter frequencies for both earth and earth-satellite scenarios. These include propagation in standard, ducting, and subrefractive atmospheres, attenuation due to the gaseous atmosphere, precipitation, and ionospheric effects. Propagation estimation techniques are given such as the Tropospheric Electromagnetic Parabolic Equation Routine (TEMPER) and Radio Physical Optics (RPO). Formulations for calculating attenuation due to the gaseous atmosphere and precipitation for terrestrial and earth-satellite scenarios employing International Telecommunication Union (ITU) models are reviewed. Case studies are presented from experimental line-of-sight, over-the-horizon, and earth-satellite communication systems. Example problems, calculation methods, and formulations are presented throughout the course for purpose of providing practical estimation tools.
The document provides details about a course on fundamentals of remote sensing, including:
- The course code, module name and code, university, and department offering the course.
- An outline of the course content and schedule, divided into 3 weeks covering topics like introduction to remote sensing, electromagnetic energy and remote sensing, satellites and image characteristics, and GPS.
- Recommended assessments including tests, lab exercises, and a group project to evaluate students' understanding of the material.
Remote sensing systems have four main types of resolution:
1. Spatial resolution determines the ability to detect fine spatial details like small objects. Higher resolution means smaller detectable objects.
2. Spectral resolution refers to the number and width of electromagnetic wavelength bands detected. Higher spectral resolution allows finer distinction between targets.
3. Radiometric resolution affects the ability to distinguish slight differences in radiation.
4. Temporal resolution is the frequency of data collection, usually days for satellites but can be more frequent depending on factors like swath overlap and latitude. Multi-temporal data is useful for observing changes over time.
1. Remote sensing involves obtaining information about an object or area through analysis of sensor data without physical contact. It has four basic components: an energy source, transmission path, target, and sensor.
2. The remote sensing process has seven elements: energy source, atmosphere, target interaction, sensor recording, transmission, interpretation, and application. Different sensors and techniques are used for passive and active remote sensing.
3. Remote sensing data can be used with GIS for applications like land use mapping, change detection, natural resource management, and hazard assessment. When combined with geospatial analysis and modeling capabilities, remote sensing and GIS are powerful tools for studying the coastal zone.
This document discusses the application of remote sensing and geographical information systems in civil engineering. It provides details on topics like resolving power, modulation transfer function, dispersing elements, spectroscopic filters, and types of spectrometers. Resolving power is defined as the minimum distance between two image points that can be detected. It depends on factors like wavelength of light and aperture diameter. The modulation transfer function describes how well an imaging system transfers contrast from the subject to the image. Dispersing elements like prisms and diffraction gratings are used to separate light into spectra. Spectroscopic filters allow only certain wavelength ranges to pass through. And spectrometers are instruments used to measure and record spectra, with types including dispersing and interference
Hyperspectral remote sensing uses narrow, contiguous bands across the electromagnetic spectrum to characterize vegetation. It is useful for studying species composition, crop/vegetation type, biophysical properties like leaf area index and biomass, biochemical properties like chlorophyll and moisture, and stress factors. Hyperspectral data comes from airborne, ground, and spaceborne sensors, with spaceborne providing global continuous coverage but at lower spatial resolution than airborne sensors. Hyperspectral data cubes contain hundreds of bands providing detailed spectral signatures to distinguish vegetation.
Application of spectral remote sensing in agronomic decision by Dr.V.Harihara...Hari Hariharasudhan
Spectral remote sensing allows for the non-destructive evaluation of plant responses to environmental stresses. Remote sensing utilizes the distinctive spectral signatures of healthy and stressed vegetation. Key plant pigments like chlorophyll strongly influence reflectance patterns and can indicate crop health. Various vegetation indices using reflectance values in different wavelength bands have been developed to retrieve agronomic parameters and assess stress from remote sensors. This provides opportunities for early and efficient monitoring of crop conditions.
1) Temperature is a measure of the average kinetic energy of particles in a substance. Higher temperatures mean particles are moving faster.
2) Absolute zero is the point where particles have no kinetic energy. Doubling the temperature doubles the average kinetic energy.
3) Heat is the transfer of thermal energy between objects due to a temperature difference. Heat flows from hotter to colder objects until thermal equilibrium is reached.
Meteorological Technology International, Jan 2010laurajairam
This document discusses advances in satellite sensor technology that enable more accurate climate monitoring from space. Specifically:
1. Prior satellite sensors had limitations like coarse spectral resolution and degrading calibration over time, making it difficult to establish long-term climate trends from space data.
2. New technologies can achieve much greater measurement accuracy, stability over decades, fine spectral resolution, and precise knowledge of spectral response needed for undisputed climate monitoring.
3. Advances like onboard high-accuracy blackbody calibration sources and hyperspectral imaging bring National Institute of Standards and Technology calibration capabilities to satellites. This eliminates prior limitations and allows climate trends to be reliably measured from space.
Errors in GPS positioning come from several sources, including ephemeris data that is up to two hours old, clock errors in satellite atomic clocks, and delays caused by signals passing through the ionosphere and troposphere. Additional errors stem from multipath interference from reflected signals, selective availability that was used by the US military, and geometry of satellite positions relative to the receiver. Most of these errors can be corrected through algorithms in the receiver but some may still cause inaccuracies of a few meters.
Remote Sensing - A tool of plant disease managementAnand Choudhary
The document provides an overview of remote sensing in plant pathology. It discusses the history and fundamentals of remote sensing, including different types of platforms, resolutions, and the objectives and case studies of remote sensing in plant disease management. Key objectives of remote sensing in plant pathology include assessing diseases over large areas, understanding disease-environment relationships, detecting and identifying plant diseases, and aiding disease management. Case studies demonstrate uses of remote sensing for various crop diseases.
This document provides an introduction to the fundamentals of remote sensing. It discusses that remote sensing involves acquiring information about the Earth's surface without direct contact, using sensors to detect reflected or emitted energy. It describes the seven elements of the remote sensing process, including an energy source, interactions with the atmosphere and target, sensor recording, data transmission and processing, interpretation, and application of results. It also discusses electromagnetic radiation, the electromagnetic spectrum, and how radiation interacts with and is scattered or absorbed by particles in the atmosphere.
This document discusses remote sensing. It defines remote sensing as acquiring information about objects without direct contact, using electromagnetic radiation. It describes how remote sensing uses platforms like aircraft and satellites to collect passive and active sensor data. It provides examples of different sensor types, including photography, infrared, LIDAR, and multispectral scanning. It also discusses important remote sensing concepts like spatial, spectral, radiometric, and temporal resolution. Finally, it highlights how the SLOSH model uses remote sensing data to accurately predict hurricane storm surges and inundation areas.
Remote sensing uses sensors on satellites and aircraft to measure electromagnetic radiation from the Earth's surface. This data can be used to support fisheries and aquaculture management by providing information on sea surface temperature, ocean color, ocean salinity, land cover, and the location of coastal aquaculture structures over large geographic areas. A case study demonstrated how satellite images could map fish ponds and cages in a coastal region of the Philippines. Remote sensing will continue playing an important role in monitoring fisheries and aquaculture by providing global and repeated observations in a cost-effective manner.
This presentation consist of remote sensing, types of remote sensing and also about the radiometers systems. I have also discussed about the types of radiometers system and how it work. I have also discussed about the principle on which it works. Also I have discussed about the applications .
Remote sensing and application by Nikhil PakwanneNIKHIL PAKWANNE
Remote sensing is the process of obtaining information about objects or areas from a distance, without physical contact. It involves the use of electromagnetic radiation to detect and classify objects on Earth through aerial sensors or satellites. The key components of a remote sensing system include an energy source, a sensor to record electromagnetic radiation, transmission of data to a receiving station, and processing to extract information. Remote sensing provides advantages like rapid coverage of large areas, accessibility to remote or dangerous regions, and collection of geo-referenced digital data. Common applications of remote sensing include agriculture, geology, urban planning, hydrology, land use mapping, forestry, and ocean monitoring.
Remote sensing in plants, botany, application in vegetation classification and conservation, basic mechanism of remote sensing,how it works, satellite mapping techniques and aerial mapping
Remote sensing uses sensors on satellites or aircraft to detect objects on Earth without physical contact. It has various applications in coastal management like mapping watersheds and resources, identifying erosion-prone areas, and monitoring coastal zones for environmental impacts. The key advantages of remote sensing for coastal management are its ability to provide synoptic and repetitive views of large areas, including during bad weather. Important satellite sensors include Landsat, SPOT, IRS and RADARSAT, which can monitor coastal geomorphology, habitats, and locate offshore fishing grounds. Innovation in sensor technology is needed to better understand and manage threats to ocean ecosystems.
Propagation Effects for Radar&Comm SystemsJim Jenkins
This three-day course examines the atmospheric effects that influence the propagation characteristics of radar and communication signals at microwave and millimeter frequencies for both earth and earth-satellite scenarios. These include propagation in standard, ducting, and subrefractive atmospheres, attenuation due to the gaseous atmosphere, precipitation, and ionospheric effects. Propagation estimation techniques are given such as the Tropospheric Electromagnetic Parabolic Equation Routine (TEMPER) and Radio Physical Optics (RPO). Formulations for calculating attenuation due to the gaseous atmosphere and precipitation for terrestrial and earth-satellite scenarios employing International Telecommunication Union (ITU) models are reviewed. Case studies are presented from experimental line-of-sight, over-the-horizon, and earth-satellite communication systems. Example problems, calculation methods, and formulations are presented throughout the course for purpose of providing practical estimation tools.
The document provides details about a course on fundamentals of remote sensing, including:
- The course code, module name and code, university, and department offering the course.
- An outline of the course content and schedule, divided into 3 weeks covering topics like introduction to remote sensing, electromagnetic energy and remote sensing, satellites and image characteristics, and GPS.
- Recommended assessments including tests, lab exercises, and a group project to evaluate students' understanding of the material.
Remote sensing systems have four main types of resolution:
1. Spatial resolution determines the ability to detect fine spatial details like small objects. Higher resolution means smaller detectable objects.
2. Spectral resolution refers to the number and width of electromagnetic wavelength bands detected. Higher spectral resolution allows finer distinction between targets.
3. Radiometric resolution affects the ability to distinguish slight differences in radiation.
4. Temporal resolution is the frequency of data collection, usually days for satellites but can be more frequent depending on factors like swath overlap and latitude. Multi-temporal data is useful for observing changes over time.
1. Remote sensing involves obtaining information about an object or area through analysis of sensor data without physical contact. It has four basic components: an energy source, transmission path, target, and sensor.
2. The remote sensing process has seven elements: energy source, atmosphere, target interaction, sensor recording, transmission, interpretation, and application. Different sensors and techniques are used for passive and active remote sensing.
3. Remote sensing data can be used with GIS for applications like land use mapping, change detection, natural resource management, and hazard assessment. When combined with geospatial analysis and modeling capabilities, remote sensing and GIS are powerful tools for studying the coastal zone.
This document discusses the application of remote sensing and geographical information systems in civil engineering. It provides details on topics like resolving power, modulation transfer function, dispersing elements, spectroscopic filters, and types of spectrometers. Resolving power is defined as the minimum distance between two image points that can be detected. It depends on factors like wavelength of light and aperture diameter. The modulation transfer function describes how well an imaging system transfers contrast from the subject to the image. Dispersing elements like prisms and diffraction gratings are used to separate light into spectra. Spectroscopic filters allow only certain wavelength ranges to pass through. And spectrometers are instruments used to measure and record spectra, with types including dispersing and interference
Hyperspectral remote sensing uses narrow, contiguous bands across the electromagnetic spectrum to characterize vegetation. It is useful for studying species composition, crop/vegetation type, biophysical properties like leaf area index and biomass, biochemical properties like chlorophyll and moisture, and stress factors. Hyperspectral data comes from airborne, ground, and spaceborne sensors, with spaceborne providing global continuous coverage but at lower spatial resolution than airborne sensors. Hyperspectral data cubes contain hundreds of bands providing detailed spectral signatures to distinguish vegetation.
Application of spectral remote sensing in agronomic decision by Dr.V.Harihara...Hari Hariharasudhan
Spectral remote sensing allows for the non-destructive evaluation of plant responses to environmental stresses. Remote sensing utilizes the distinctive spectral signatures of healthy and stressed vegetation. Key plant pigments like chlorophyll strongly influence reflectance patterns and can indicate crop health. Various vegetation indices using reflectance values in different wavelength bands have been developed to retrieve agronomic parameters and assess stress from remote sensors. This provides opportunities for early and efficient monitoring of crop conditions.
1) Temperature is a measure of the average kinetic energy of particles in a substance. Higher temperatures mean particles are moving faster.
2) Absolute zero is the point where particles have no kinetic energy. Doubling the temperature doubles the average kinetic energy.
3) Heat is the transfer of thermal energy between objects due to a temperature difference. Heat flows from hotter to colder objects until thermal equilibrium is reached.
This document contains 17 trivia questions about various topics including sports, history, literature and politics. It tests knowledge on details such as the number of players on a rugby team, the location of Chelsea's stadium, key figures and events from World War 2 like Winston Churchill and the invasion of Poland, and authors of famous books like Jules Verne and William Shakespeare. The questions cover a wide range of people, places, and time periods to challenge general knowledge.
1. O documento descreve um projeto de uma turbina eólica de eixo vertical para aplicação em meio urbano. Inclui análise aerodinâmica, resultados de cálculo de coeficientes de potência e projeto estrutural da turbina.
2. A análise aerodinâmica usa modelos matemáticos para calcular coeficientes de potência variando a velocidade de rotação e fator de bloqueamento, e estuda perfis multi-elementos usando o Javafoil.
3. Inclui também projeto
Gore performed temperature cycling tests on four identical junction boxes to evaluate the performance of GORE Protective Vents. The tests subjected the boxes to extreme temperature fluctuations over 10 days. Boxes with vents maintained constant internal pressure and reduced humidity levels. Unvented boxes experienced seal failure and increased humidity, demonstrating the importance of ventilation for extending product life in harsh environments.
The document discusses PythonTeX, a LaTeX package that allows Python code to be executed and included in LaTeX documents. PythonTeX allows LaTeX documents to function not just as text formatters but also as programming, data analysis, and calculation tools. It introduces basic Python commands that can be used in LaTeX like \py, \pyc, \pyb to execute Python code and include outputs. Examples are provided of mathematical operations, printing messages, and handling errors in the PythonTeX environment.
This presentation consists of slides with text and outlines about various topics. It includes slides on a math theorem, definitions, and lorem ipsum passages. The presentation outlines sections on an important story, problems, solutions, and facts, but provides minimal details in the slides themselves. It appears to be a template presentation with placeholder text and outlines to be filled in.
This document discusses conventions used in music videos that increase repeatability from the audience's perspective. It discusses four key conventions:
1. Sexualizing women to appeal to male viewers while potentially offending female viewers. This represents the song lyrics visually.
2. Showing artists actually playing instruments to appear authentic and gain audience dedication to the music.
3. Matching visuals in the video to lyrics in the song to make the video and song easier to understand and follow.
4. Balancing focus between performance and narrative to maintain audience interest without losing the storyline or performers. This provides a good dosage of both elements.
The document argues that employing these conventions can increase how appealing and enjoyable
The document discusses creating and using bibliographic databases with BibTeX. It explains that BibTeX allows storing bibliographic references in one or more .bib files and generating citations and a bibliography by specifying these files in a LaTeX document. It provides examples of common BibTeX styles and describes the structure and fields of .bib database entries. The document also outlines the basic steps for running LaTeX and BibTeX together to include a bibliography in a document.
This document discusses the Indian TEX Users Group and provides an on-line tutorial on LTEX. The tutorial team consists of professors and staff from various universities and technology companies in India. The document was generated using LTEX and various packages. It may be distributed under the terms of the LTEX Project Public License.
This document provides an overview of inserting and formatting floating figures in LaTeX. It discusses the figure environment for creating floats, placement options like [h], [t], [b], and [p], and counters and fractions for customizing float placement. Graphics formats like EPS can be included using \includegraphics, and graphics paths and extensions can be specified. Finally, it describes rotating and scaling objects with commands like \rotatebox and \scalebox.
This document is a presentation template for the Technical Faculty at FAU titled "Theme for the Technical Faculty". It was created by Alexander Zhou on January 28, 2015. The presentation contains 4 slides, including two sample slides showing formatted text and images that could be used in a presentation for the Technical Faculty.
The document summarizes the results of a questionnaire given to vegetarians and vegans to gather research for creating recipe cards. Key findings include: most chose the vegetarian/vegan lifestyle due to animal welfare concerns; most cook their own meals; curry is a preferred meal; tofu will be used instead of Quorn to appeal to vegans; some will occasionally eat vegan; and oriental recipes will be featured to change perceptions. This research informed the recipe selection to best suit the target audience.
This document contains 17 trivia questions about various topics including sports, history, literature and politics. It tests knowledge on details such as the number of players on a rugby team, the location of Chelsea's stadium, key figures and events from World War 2 like Winston Churchill and the invasion of Poland, and authors of famous books like Jules Verne and William Shakespeare. The questions cover a wide range of people, places, and time periods to challenge general knowledge.
This document contains 17 trivia questions about various topics including sports, history, literature and politics. It tests knowledge on details like the number of players on a rugby team, the location of Chelsea's stadium, key figures and events in World War 2 and more. The questions are multiple choice or short answer format with the answers provided.
Buku ini membahas penggunaan LaTeX untuk membuat puisi, lagu, dan permainan seperti teka-teki silang menggunakan bahasa pemrograman LaTeX. Buku ini ditujukan untuk pembaca yang sudah menguasai dasar-dasar LaTeX.
Андрій Маштаков: "Інструменти і корисні поради"Volyn Media
Презентація експерта з нових медіа Андрія Маштакова під час тренінгу «Механізми громадського моніторингу та можливості застосування нових медіа у цьому процесі», що відбувся 14 червня 2013 р. у м. Луцьку в конференц-залі «ВолиньМедіа»
On the Performance of Filters for Reduction of Speckle Noise in SAR Images Of...Zac Darcy
Synthetic Aperture Radar (SAR) imagery to monitor oil spills are some methods that have been proposed
for the West African sub-region. With the increase in the number of oil exploration companies in Ghana
(and her neighbors) and the rise in the coastal activities in the sub-region, there is the need for proper
monitoring of the environmental impact of these socio-economic activities on the environment.Detection
and near real-time information about oil spills are fundamental in reducing oil spill environmental impact.
SAR images are prone to some noise, which is predominantly speckle noise around the coastal areas. This
paper evaluatesthe performance of the mean and median filters used in the preprocessing filtering to
reduce speckle noise in SAR images for most image processing algorithms
Exploring ImageJ toolbox for Oceanography: A case study in Malacca StraitsIRJESJOURNAL
Abstract: The oil discharges in marinas and coastal areas has adversely affected the marine environment that has become the driving force for the early detection of oil spills to allow timely intervention. Synthetic Aperture Radar (SAR) data represents an effective tool that is extensively used for the detection and identification of oil spills in the marine environment. This paper aims at exploring the plugins available in ImageJ, a popular public domain Java image processing and analysis program at the National institute of Health (NIH), in the detection of oil spills for oceanography. As the popularity of the ImageJ open-source comes from being extensively used in biomedical and medical image processing applications, this study showed that ImageJ is a good choice for the detection of oil spills in oceanography applications throughout the extensibility capability supported by ImageJ framework.
The document reviews techniques for reducing speckle noise in synthetic aperture radar (SAR) data. It begins by describing the characteristics of speckle noise and its multiplicative nature. It then discusses common spatial domain filtering techniques for SAR data denoising, including Lee filtering, Frost filtering, and Kuan filtering. These are adaptive filters that estimate pixel values based on statistics within a moving window. The document also reviews wavelet-based denoising techniques and their advantages over spatial domain filters, including better preservation of edges. Finally, it provides an overview of future research opportunities in developing new speckle reduction methods.
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known that SAR can provide several times better image resolution than conventional radars. The exploration for efficient
image denoising methods still remains a valid challenge for researchers. Despite the difficulty of the recently proposed
methods, mostly of the algorithms have not yet attained a pleasing level of applicability; each algorithm has its
assumptions, advantages, and limitations. This paper presents a review of synthetic aperture radar. Behind a brief
introduction in our work we are especially targeting the noise called backscattered noise in SAR terminology which
causes the appearance of speckle Potential future work in the area of air flight navigation, mapping Weather Monitoring
& during natural disaster like earth quake. The SAR having the capability, to make human visibility beyond optical
vision, is also discussed.
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satellite image is one of the challenges encountered in the detection of shoreline. An efficient framework
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images.
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The document discusses various techniques for removing speckle noise from images, which is a type of noise that inherently exists in synthetic aperture radar (SAR) images. It describes common speckle noise removal methods like median filters, Wiener filters, Frost filters, and Lee filters. The document concludes that the Wiener filter is generally best for removing speckle noise as it minimizes the mean square error when filtering.
Computationally Efficient Methods for Sonar Image Denoising using Fractional ...CSCJournals
Sonar images produced due to the coherent nature of scattering phenomenon inherit a multiplicative component called speckle and contain almost homogeneous as well as textured regions with relatively rare edges. Speckle removal is a pre-processing step required in applications like the detection and classification of objects in the sonar image. In this paper computationally efficient Fractional Integral Mask algorithms to remove the speckle noise from sonar images is proposed. Riemann- Liouville definition of fractional calculus is used to create Fractional integral masks in eight directions. The use of a mask incorporated with the significant coefficients from the eight directional masks and a single convolution operation required in such case helps in obtaining the computational efficiency. The sonar image heterogeneous patch classification is based on a new proposed naive homogeneity index which depends on the texture strength of the patches and despeckling filters can be adjusted to these patches. The application of the mask convolution only to the selected patches again reduce the computational complexity. The non-homomorphic approach used in the proposed method avoids the undesired bias occurring in the traditional homomorphic approach. Experiments show that the mask size required directly depends on the fractional order. Mask size can be reduced for lower fractional orders thus ensuring the computation complexity reduction for lower orders. Experimental results substantiate the effectiveness of the despeckling method. The different non reference image performance evaluation criterion are used to evaluate the proposed method.
UNDER WATER NOISE REDUCTION USING WAVELET AND SAVITZKY-GOLAYcsandit
This summary provides the key details from the document in 3 sentences:
The document discusses two methods for reducing noise in underwater acoustic signals used for depth estimation: wavelet-based denoising using stationary wavelet transform and Savitzky-Golay filtering. It analyzes the performance of different wavelet types and polynomial orders/frame sizes for the two filtering methods based on peak signal-to-noise ratio. The results show that Harr wavelet and higher order polynomials with smaller frame sizes provided better noise reduction for the underwater depth estimation signals.
Time-Frequency Attenuation of Swell Noise on Seismic Data from Offshore Centr...iosrjce
Diversity of noise types with different characteristics makesseparation of signal and noise a
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code) processing approach was used to attenuate swell noise on dataset from a marine seismic survey
offshoreCentral Niger-Delta, Nigeria, which shows as an effective amplitude preserving and robust tool that
gives better results compared to many other conventional filtering algorithms.With this processing approach
and working side-by-side with the shot gather and the RMS windows; the results achieved are reliable and
satisfactory by giving clearer images for reservoir characterization. The level of swell noise attenuation after
this approach greatly increased the confidence to use the data for subsequent processing steps.
Noise removal techniques for microwave remote sensing radar data and its eval...csandit
Microwave Remote Sensing data acquired by a RADAR sensor such as SAR(Synthetic Aperture
Radar) is affected by a peculiar kind of noise called speckle. This noise not only renders the
data ineffective for classification, texture analysis, segmentation etc. which are used for image
analysis purposes, but also degrades the overall contrast and radiometric quality of the image.
Here we discuss the various noise removal techniques which have been widely used by scientists
all over the world. Different filtering methods have their pros and cons, and no single method
can give the most satisfactory result. In order to circumvent those issues, better and better
methods are being attempted. One of the recent methods is that based on Wavelet technique.
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those methods. The relative merits and demerits of the filters and their evaluation is also done.
NOISE REMOVAL TECHNIQUES FOR MICROWAVE REMOTE SENSING RADAR DATA AND ITS EVAL...cscpconf
Microwave Remote Sensing data acquired by a RADAR sensor such as SAR(Synthetic Aperture Radar) is affected by a peculiar kind of noise called speckle. This noise not only renders the
data ineffective for classification, texture analysis, segmentation etc. which are used for image analysis purposes, but also degrades the overall contrast and radiometric quality of the image. Here we discuss the various noise removal techniques which have been widely used by scientists all over the world. Different filtering methods have their pros and cons, and no single method can give the most satisfactory result. In order to circumvent those issues, better and better methods are being attempted. One of the recent methods is that based on Wavelet technique. This paper discusses the denoising techniques based on Wavelets and the results from some of those methods. The relative merits and demerits of the filters and their evaluation is also done.
IRJET- Analysis of Underwater Image Visibility using White Balance AlgorithmIRJET Journal
1) The document discusses several techniques for analyzing and improving the visibility of underwater images, including white balancing algorithms, red channel methods, and image fusion approaches.
2) White balancing aims to remove unwanted color casts to improve image aspects like color and contrast. Image fusion techniques combine input images and weight maps to enhance color contrast and visibility of distant objects degraded by the underwater medium.
3) The techniques were evaluated using metrics like PSNR and by comparing restored images to originals. Results found white balancing produced high accuracy recovery of important faded features while image fusion generally improved global contrast, color, and details.
1) The document describes a wavelet-based technique for denoising underwater signals affected by wind-driven ambient noise. It uses discrete wavelet transform to decompose the noisy signal into coefficients. 2) A threshold is calculated using the universal threshold method and applied to the coefficients to remove noise. Hard and soft thresholding are evaluated. 3) The denoised signal is then reconstructed from the modified coefficients using inverse discrete wavelet transform. The technique is shown to effectively reduce wind noise and improve the signal-to-noise ratio.
1) The document describes a wavelet-based technique for denoising underwater signals affected by wind-driven ambient noise. It uses discrete wavelet transform to decompose the noisy signal into coefficients. 2) Thresholding is then applied to the coefficients, where threshold values are calculated separately for each level of decomposition using universal thresholding. 3) The signal is then reconstructed from the modified coefficients after thresholding to reduce noise. The technique aims to improve the signal-to-noise ratio of underwater signals corrupted by wind noise.
Performance of Various Order Statistics Filters in Impulse and Mixed Noise Re...sipij
Remote sensing images (ranges from satellite to seismic) are affected by number of noises like interference, impulse and speckle noises. Image denoising is one of the traditional problems in digital image processing, which plays vital role as a pre-processing step in number of image and video applications. Image denoising still remains a challenging research area for researchers because noise
removal introduces artifacts and causes blurring of the images. This study is done with the intension of designing a best algorithm for impulsive noise reduction in an industrial environment. A review of the typical impulsive noise reduction systems which are based on order statistics are done and particularized for the described situation. Finally, computational aspects are analyzed in terms of PSNR values and some solutions are proposed.
Lake sediment thickness estimation using ground penetrating radareSAT Publishing House
This document summarizes a study that used ground penetrating radar (GPR) to estimate the thickness and volume of sediments in Punem Lake, India. GPR profiles identified two sediment layers in the lake. The thickness of the first layer ranged from 0.02m to 1.16m with an average of 0.5m, while the second layer ranged from 0.08m to 0.99m with an average of 0.37m. Sediment volume was estimated at 260,303 cubic meters for the first layer and 188,171 cubic meters for the second layer. Thicker sediments were found toward the north, northeast, and east of the lake for the first layer and toward the north, northeast, and west for
This presentation was made on August 5, 2008 at the University of California, Santa Barbara. It discusses airborne hyperspectral technologies and applications.
This document discusses a novel technique for better analysis of ice properties using Kalman filtering. It summarizes previous research on sea ice segmentation using SAR imagery and dual polarization techniques. It proposes using an automated SAR algorithm along with Kalman filtering to more accurately detect sea ice properties from RADARSAT1 and RADARSAT2 imagery data. The document reviews techniques for image segmentation, dual polarization, PMA detection, and related work on sea ice classification using statistical ice properties, edge preserving region models, and object extraction methods.
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On the performance of filters for reduction of speckle noise in sar images off the coast of the gulf of guinea
1. International Journal of Information Technology, Modeling and Computing (IJITMC) Vol.1,No.4,November 2013
ON THE PERFORMANCE OF FILTERS FOR
REDUCTION OF SPECKLE NOISE IN SAR
IMAGES OFF THE COAST OF THE GULF OF
GUINEA
KlogoGriffith S.1, GasonooAkpeko2 and Ampomah K. E. Isaac3
1,2,3
Department of Computer Engineering Kwame Nkrumah University of Science and
Technology, KNUST, Kumasi, Ghana
ABSTRACT
Synthetic Aperture Radar (SAR) imagery to monitor oil spills are some methods that have been proposed
for the West African sub-region. With the increase in the number of oil exploration companies in Ghana
(and her neighbors) and the rise in the coastal activities in the sub-region, there is the need for proper
monitoring of the environmental impact of these socio-economic activities on the environment.Detection
and near real-time information about oil spills are fundamental in reducing oil spill environmental impact.
SAR images are prone to some noise, which is predominantly speckle noise around the coastal areas. This
paper evaluatesthe performance of the mean and median filters used in the preprocessing filtering to
reduce speckle noise in SAR images for most image processing algorithms.
KEYWORDS
SAR images, Mean filter, Median filter, Speckle noise, MSE and PSNR
1. INTRODUCTION
The West African sub-region is one of the active oil exploration regions in the world, with
countries such as Nigeria, Ghana, Ivory Coast, Democratic Republic of Congo Cameroon and
Equatorial Guinea been the major producers. The Gulf of Guinea countries are estimated to
produce about 4% of the global total of oil per day, with Nigeria producing more than half of the
total for the sub-region [1]. Ghana as a country is not new to oil exploration, the country’s oil
exploration dates back to about a century in the saltpond fields.Ghana discovered oil in
commercial quantities in June 2007. However, with the increase in the number of oil exploration
companies in Ghana (and her neighbors) and the rise in the coastal activities in the sub-region,
there is the need for proper monitoring of the environmental impact of these socio-economic
activities on the environment. The increase in the exploration activities in the sub-region as
shown in figure 1and figure 2 comes with its attendant effects of oil spills which are usually
intentional or accidental.
DOI : 10.5121/ijitmc.2013.1405
43
2. International Journal of Information Technology, Modeling and Computing (IJITMC) Vol.1,No.4,November 2013
Fig.1: Oil Exploration in the Gulf of Guinea [2]
Fig.2: Discovery and Exploration fields in The Gulf of Guinea [3]
Oil spills can come from various sources including leakage from oil transportation tankers,
accidents on oil platforms and seepage from natural seeps.Oil spills are getting more and more
frequent on the sea surface. Annually, 48% of the oil pollution in the seas is caused by fuels and
29% by crude oil. Tanker accidents contribute with only 5% of the all pollution entering into the
sea [4]. Timely, accurate and continuous detection of oil spills in the sub-region can help
management and monitoring of oil spills.Remote sensing does provides fast and reliable
measurement of the ocean’s surface waters, and thus has been used widely to assess oil pollution
at sea, as well as other water bodies. The remote sensing instruments include optical, microwave,
and radar (e.g., Synthetic Aperture Radar, SAR) sensors which can be airborne and
satellites.Airborne remote sensing offers the highest resolution and fastest response in
measurements, but often very expensive to be used for operational monitoring. In contrast,
satellite remote sensing provides reliable measurements of the ocean at a reasonable cost, hence
44
3. International Journal of Information Technology, Modeling and Computing (IJITMC) Vol.1,No.4,November 2013
more suitable for oil spill monitoring [5]. SAR is frequently used for oil spill detection at sea,
compared to the various satellite instruments. The sea-surface echo radar signal is modulated by
the wind-induced capillary waves, and thus carries detailed information on the surface roughness
[6], giving the degree of oil spill on the surface of the sea. Due to the difference in the surface
tensions of water and oil, there is also a difference in the backscattered signals that is received by
the instrument.Oil film on the ocean surface has higher surface tension than water, and
doesreduce the surface capillary waves, resulting in a smoother sea surface. The irregularity of
the radar echo signal makes the oil contaminated areas appear as dark patches in SAR
images.SAR is an all-weather and all-day high resolution aerial and space imaging of terrain.
Being independent of light and weather conditions, SAR images does perform better than optical
images hence its efficiency for detecting various ocean surface features such as oil spills. The
backscattered or radar echo energy level for oil spilled areas received in the SAR systems is too
low since the oil reduces the capillary waves of the sea surface. However, other natural
phenomenon also contributes to damping the short waves and creates dark areas of the sea surface
in the SAR images. Some of these natural phenomenons that create dark areas on the sea surface
are due to suspension of Bragg scattering mechanism depending on ocean and/or atmospheric
conditions [6]. Atmospheric conditions also contribute to noise in the SAR images, which affects
the interpretation and/or feature extraction from the images. Signals received by radar are usually
contaminated by noise due to random modulation of the radar pulse during atmospheric
propagation, or due to fluctuation in the receiving circuits.
2. NOISE AND NOISE REDUCTION
Noise is a random and usually an unwanted signal in a lot of applications: it can be experienced in
acoustics signals, picture and video signals. Noise is evident in the variation in brightness or color
information in a picture or a video sequence. Noise is most obvious in regions with low signal
level, such as the weak received echo-signal in a radar receiver. Noise is characterized by its
statistical properties. Noise containing all frequencies with equal amplitudes called “white” noise
is typical in picture and video applications. Radar images are often corrupted by these random
variations in intensity values. Some common types of noise are salt and pepper noise, impulse
noise, and Gaussian noise.Some of the noise that affects SAR images includes Speckle Noise and
Gaussian Noise. To better perceive images, noise reduction techniques need to be applied to
reduce the unwanted areas of the image.
2.1. Speckle Noise
Speckle noise is a coarse noise that is usually evident in and degrades the quality of the active
radar and synthetic aperture radar (SAR) images. Radar waves can interfere constructively or
destructively to produce light and dark pixels in radar image. Speckle noise is commonly
observed in radar sensing system and images, although it can be observed in most types of
remotely sensed images utilizing coherent radiation. Speckle noise in radar data or images have
multiplicative error and must be removed before the data can be used otherwise the noise is
merged into and degrades the image quality.
45
4. International Journal of Information Technology, Modeling and Computing (IJITMC) Vol.1,No.4,November 2013
3. FILTERS
Broadly filters are designed to remove unwanted components from a set of signals, they can be
devices or processes. In image processing, filters are used to improve the quality of images prior
to its usage. Filtering is also sometimes referred to as smoothing, which is done to reduce noise
and improve the image quality.Depending on the type of noise, linear or nonlinear filters are
employed to remove the noise. Linear filters are good filters for removing Gaussian noise
andother types of noise in most cases as well. Linear filters are implemented using the weighted
sum of the pixels in successive windows of the image. Nonlinear filters are those that are
implemented without a weighted sum of pixels. Nonlinear filters are usually spatially invariant,
which implies that the same calculation is performed at all parts of the image. The Mean and
Median filters are typical linear and nonlinear filters employed in image processing respectively.
3.1. Mean filter
Mean or Average filter is one of the simplest linear filters that is implemented by performing
local averaging operation as shown in equation 1 and the value of each image pixel is replaced by
the average of all the values in the local neighborhood [7][8]. The mean filter works as low-pass
one.
h[i, j ]
1
M
f [k , l ]
1
( k , l )N
whereM is the number of pixels in the surrounding N, h[i,j] and f[k,l] are the old and new image
pixels.The size of the neighborhood N controls the degree of filtering. A large neighborhood size
will result in a greater degree of filtering.
3.2. Median filter
The median filter is a nonlinear filter usually spatially invariant, which replaces each pixel value
with the median of the pixel values in the local neighborhood [7]. The median filter is very
effective in retaining the image details since they do not depend on values which are significantly
different from typical values in the neighborhood. The median filter works on consecutive image
window in a manner similar to that of the linear filters, but the method employed does not use a
weighted sum.Pixels in each window are sorted into ascending order and the pixel value in the
middle is selected as the new value for a particular pixel.
4. PERFORMANCE METRICS
Performance of filters can be estimated using numerical measures of picture quality after the filter
has been applied to the image. The performance metrics are chosen based on their computable
distortion measures.Mean squared error (MSE) and Peak Signal to Noise Ratio (PSNR) are by far
the most common measures of picture quality in image systems [9] [10].
4.1. Mean-Square Error (MSE)
The easiest and widely used image quality metric is the mean squared error (MSE), computed by
averaging the squared intensity differences of distorted and reference image pixels. MSE
46
5. International Journal of Information Technology, Modeling and Computing (IJITMC) Vol.1,No.4,November 2013
application adopts an assumption that the reduction of perceptual quality of an image is
directlyrelated to the visibility of the error signal. The image signal whose quality is being
evaluated is thought of as a sum of an accurate reference signal and an error signal [10].MSE can
objectively quantify the strength of the error signal present in an image after a filter is applied to
the same image. The mean squared error (MSE) for practical purposes, allows comparison of the
pixel values of imagesafter filtering to the degraded image before filtering.
4.2. Peak Signal-to-Noise Ratio (PSNR)
Peak signal-to-noise ratio (PSNR) of an image is a relation for the ratio between the maximum
value (power) of a signal and the power of distorting noise that disturbs the quality of its image
[11]. Peak signal-to-noise ratio (PSNR) is a related quality metric which is usually used along
with MSE. These two are appealing due to the simplicity to calculate, easy physical meanings and
mathematically convenient in the context of optimization [10].
5. EVALUATION OF MEAN AND MEDIAN FILTERS ON SPECKLE
NOISE
The mean and median filters are compared to evaluate their performance in the reduction of
speckle noise in SAR images. The filters are evaluated using image pixel window size of 3X3 in
MATLAB, while introducing various percentage of speckle noise into the image.The original
image in RGB is shown in figure 3 and the gray level of the image with the histogram distribution
is shown in figure 4 and 5 respectively. The image with 50% speckle noise with the histogram
distribution is shown in figure 6 and 7 respectively.
Fig. 3: SAR image (RGB) without speckle noise
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Fig. 4: SAR image (gray) without speckle noise
Fig. 5: Histogram distribution of SAR image (gray) without speckle noise
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Fig. 6: SAR image (gray) with speckle noise
Fig. 7: Histogram distribution of SAR image (gray) with speckle noise
6. PERFORMANCE OF MEAN AND MEDIAN FILTERS ON
SPECKLE NOISE
In comparing the performance of the mean and median filters on the reduction of speckle noise,
MSE and PSNR was used.Table 1 and 2 summarizes the performance of the mean and median
filters for the various levels of speckle noise. Figure 8 and 9 are graphical simulation showing the
performance of the mean and median filters with reference to MSE and PSNR respectively.
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Table 1: Comparison of PSNR for mean and median filters
Table 2: Comparison of MSE for mean and median filters
Fig. 8: Graph of comparison of MSE for mean and median filters
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Fig. 9: Graph of comparison of PSNR for mean and median filters
7. DISCUSSION OF RESULTS
In the comparison of the performance of the mean and median filters on the reduction of speckle
noise in SAR images, various degrees of speckle noise was introduced into the image from 1% to
90%. Using an image pixel window size of 3X3, the results for MSE show that the mean filter
performs better than the median filter when the noise level is below 10% as shown in figure 8.
The median filter performs better than the mean filter for high levels of noise for both the MSE
and PSNR as shown in figure 8 and 9.
8. CONCLUSION
In this paper, the mean and median filters were compared to evaluate their performance in
reduction of speckle noise typical in radar images like SAR images. The simulation results show
that the median filters performs better for high levels of speckle noise in the SAR image. The
mean filter is performs very well in terms of MSE when the noise levels are low. Therefore,
designing an adaptive algorithm which will take advantage of the strengths of both the mean and
median filters will be a possible future research direction.
REFERENCES
[1]
[2]
[3]
Gulf of Guinea: The new Wild West, http://www.pipelinedreams.org/2011/05/gulf-of-guinea-thenew-wild-west/ , Accessed on 13th August 2013.
Ghana: Accra Joint Venture awards drilling contract for Starfish-1 well offshore Ghana
http://www.energy-pedia.com/news/ghana/new-154151, Accessed on 13th August 2013.
Geology and Total Petroleum Systems of the Gulf of Guinea Province of West Africa, http://ivg.livejournal.com/292879.html, Accessed on 13th August 2013.
51
10. International Journal of Information Technology, Modeling and Computing (IJITMC) Vol.1,No.4,November 2013
L. M. Hang and N. D. Duong, “Oil Spill Detection and Classification by ALOS PALSAR at Vietnam
East Sea”, 7th FIG Regional Conference, Spatial Data Serving People: Land Governance and the
Environment – Building the Capacity, Hanoi, Vietnam, 19-22 October 2009, pp 1-12.
[5] H. Chuanmin, L. Xiaofeng& W. G. Pichel, “Detection of Oil Slicks using MODIS and SAR
Imagery”, Handbook of Satellite Remote Sensing Image Interpretation: Marine Applications, College
of Marine Science, University of South Florida, 140 7th Ave., S., St. Petersburg, FL 33701 USA.
[6] C. Ozkan, B. Osmanoglu, F. Sunar G. Staples, K. Kalkan and F. BalikSanli, “Testing the
Generalization Efficiency of Oil Slicks Classification Algorithm Using Multiple SAR Data for
Deepwater Horizon Oil Spill”, international Archives of the Photogrammetry, Remote Sensing and
Spatial Science, Vol. XXXIX-B7, 2012 XXII ISPRS Congress, 25 August – 01 September 2012,
Melbourne, Australia, pp 67-72.
[7] Tamal Bose, “Digital Signal and Image Processing” Utah State University, John Wiley & Sons, Inc.
[8] H. Huang, C. Chen, S. Wang and H. H Lu, “Adaptive symmetric mean filter: a new noise-reduction
approach based on the slope facet model”, APPLIED OPTICS , Vol. 40, No. 29, 10 October 2001, pp
5192 – 5205.
[9] S. Grgic, M. Grgicand M. Mrak, “Reliability of Objective Picture Quality Measures”, Journal of
ELECTRICAL ENGINEERING, VOL. 55, NO. 1-2, 2004, 3-10, pp 3 – 10
[10] Z. Wang, Member, IEEE, A. C. Bovik, Fellow, IEEE, H. R. Sheikh, Student Member, IEEE, and E.
P. Simoncelli, Senior Member, IEEE, “Image Quality Assessment: From Error Visibility to Structural
Similarity”, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 13, NO. 4, APRIL 2004, pp
1 – 14.
[11] National Instruments “Peak Signal-to-Noise Ratio as an Image Quality Metric”, Publish Date: Jun 18,
2012
[4]
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