This document discusses band ratios, band combinations, and principal component analysis (PCA) in remote sensing. It defines band ratios as dividing pixel values in one spectral band by corresponding values in another band. Ratios can help differentiate between stressed and non-stressed vegetation. Common Landsat band combinations for RGB displays are also described, such as 4,5,3 which enhances vegetation and land/water boundaries. PCA is introduced as a technique to reduce the dimensionality of data while retaining variation; it was originally developed in 1933 and has various applications in data analysis.
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
In this work, a Split Ring Resonator (SRR) unit cell is simulated in a waveguide with electromagnetic field solver High Frequency Structure Simulator (HFSS). Analytical calculations of the inductance and capacitance have been also carried out to obtain the resonant frequencies for SRR dimensions. A comparison between calculated and simulated resonance frequencies)) is done. A good correlation between simulated and measured resonance frequencies is achieved.
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
In this work, a Split Ring Resonator (SRR) unit cell is simulated in a waveguide with electromagnetic field solver High Frequency Structure Simulator (HFSS). Analytical calculations of the inductance and capacitance have been also carried out to obtain the resonant frequencies for SRR dimensions. A comparison between calculated and simulated resonance frequencies)) is done. A good correlation between simulated and measured resonance frequencies is achieved.
21 15036 design of planar dielectric resonator antenna array at 28 g hz(edit)nooriasukmaningtyas
This article presents a planar array of rectangular Dielectric Resonator Antenna operating for 28 GHz applications. The proposed antenna is formed through two stages of designs which are a single element and planar array. It is made up from a ceramic material with a dielectric constant of 10 and mounted on RT/Duroid 5880 with a relative permittivity of 2.2 and a thickness of 0.254 mm. A prospective study using three different configurations of three by three planar array is done in order to obtain the best performance in terms of bandwidth, gain, and cost reduction. Besides that, this study is also conducted for a beam steering capability of each configuration. Finally, the best configuration is proposed for 5G application.
Numerical parametric study on interval shift variation in simo sstd technique...eSAT Journals
Abstract SSTD (Single Station Time Domain) technique is one of the efficient methods used to extract modal parameters of a structure. Instead of extracting the parameters in frequency domain by utilising Fast Fourier Transform (FFT) as used by some other methods, this technique only relies on free decay responses to obtain the required parameters. In this paper, a parametric study on time shift interval on algorithm method is investigated. The accuracy assessment is made using simulated analytical data with known properties where percentage error between the results of simulated and this method can be calculated and compared. Keywords: SSTD (Single Station Time Domain), FFT, EMA
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Abstract
Terahertz sub-surface imaging offers an effective solution for surface and 3D imaging because of minimal
sample preparation requirements and its ability to “see” below the surface. Another important property is the ability
to inspect on a layer-by layer basis via a non-contact route, non-destructive route. Terahertz 3D imager designed
at Applied Research and Photonics (Harrisburg, PA) has been used to demonstrate reconstructive imaging with a
resolution of less than a nanometer. Gridding with inverse distance to power equations has been described for 3D
image formation. A continuous wave terahertz source derived from dendrimer dipole excitation has been used for
reflection mode scanning in the three orthogonal directions. Both 2D and 3D images are generated for the analysis
of silver iodide quantum dots’ size parameter. Layer by layer image analysis has been outlined. Graphical analysis
was used for particle size and layer thickness determinations. The demonstrated results of quantum dot particle
size checks well with those determined by TEM micrograph and powder X-ray diffraction analysis. The reported
non-contact measurement system is expected to be useful for characterizing 2D and 3D naomaterials as well as for process development and/or quality inspection at the production line.
Preparation and characterization of nimesulide loaded cellulose acetate hydro...Jing Zang
The aim of this study is to prepare nimesulide loaded cellulose acetate hydrogen phthalate nanoparticles by salting out technique. In this study Cellulose acetate Hydrogen phthalate was taken as polymer. Nimesulide was selected as a model drug. This technique is suitable for drugs and polymers that are soluble in polar solvents such as acetone or ethanol. The effect of drug concentration and polymer concentration on nanoparticle size, shape, uniform size distribution and stability was studied. Nanoparticles were evaluated for particle size, zetapotential and particle size distribution. Size of the particle was measured by SEM.(Scanning electron microscope).Surface charge and stability of the resultant nanoparticles was determined by Zetasizer. Particle size distribution was determined by Photon Correlation Spectroscopy (PCS) with a Malvern Zetasizer Nano-ZS. The cellulose acetate hydrogen phthalate concentration and nimesulide concentration was varied from 5mg/ml to 10 mg/ml. The effect of drug and polymer concentrations on nanoparticle size, shape, particle size distribution was studied. Increased drug concentration has no impact on the particle size. The size of the particle was found to be decreased with increased polymer concentration. Increased polymer concentration has resulted in uniform particle size distribution. Higher the polymer concentrations and lower the drug concentrations resulted in uniform particle size distribution.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Design of Symmetric dispersion compensated, long haul, Single and Multichanne...IOSR Journals
Abstract: Here we propose a model on Enhanced- Large Effective Area Fiber (E-LEAF) and Dispersion Compensation Module (DCM) with precise designed Dispersion Compensation Fiber (DCF). The Model is implemented in a long haul Single and Multichannel Optical telecommunication systems with E-LEAF as data transmission Fiber (NZ-DSF) of 1700Km (85 Km SMF×20 loops) length. The DCM is proposed in Symmetric Compensation fashion consisting of 20Km (2Km×20spans) length DCF in Pre-Compensation and Post-Compensation totally comprising of 40Km length DCF for complete Compensation of total Optical Link. Thereby, we study the effect of various Line Coding Schemes like NRZ, RZ, CS-RZ, DUOBINARY and MODIFIED DUOBINARY in single and multichannel optical link with our designed DCM and concluded the suitable line coding scheme for our proposed model. This paper focus on the theoretical background, design procedures, technical terms and finally a simulation model is experimented with proposed parameters to realize the foresaid concepts with various modulation formats.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Comparison of PMD Compensation in WDM SystemsIOSR Journals
The need for larger capacities in long haul optical digital transmission lead to greater channel
density which can be achieved by wavelength division multiplexing and increasing the bit rate of each channel.
As data rates increases, certain phenomena such as dispersion began to show up as obstacles. At higher bit
rates beyond 2.5Gbps polarization mode dispersion (PMD) becomes a main factor in the degradation of the
transmission characteristics. PMD occurs when slightly different planes of light inside a fiber travel at slightly
different speeds and make it impossible to transmit data reliably at high speed in single mode fibers. PMD is
caused due to optical birefringence in the fiber due to which the two modes within a single mode fiber travel
with different group velocities and the random change of this birefringence along the fiber length results in
random coupling between the modes. This effect of PMD results in broadening of transmitted pulses that limit
the transmission capacity of the fiber. In high-speed optical communication systems working at data rates of
10Gbps and beyond, signal distortion caused by PMD is also a major limitation of the transmission distance.
This paper intends to analyze the performance of PMD compensation by optical compensation technique and
using DCF in a two channel WDM system. The analysis is done through eye diagrams from which the Q value
and bit error rate can be determined by simulating with OptSim5.3, which includes the latest simulation
algorithms to guarantee the highest possible accuracy and real world results
16 15032 hight order ijeecs 1570310229 (manuscript)(edit)nooriasukmaningtyas
The excitation of the higher-order mode, 〖〖TE〗^y〗_1δ3 in rectangular dielectric resonator designed was explored to enhance the antenna gain and detailed elaboration is presented in this paper. The antenna was fed by a 50Ω microstrip line through an aperture cut in the ground plane. Besides avoiding spurious radiation, this feeding technique gives flexibility in controlling the amount of coupling in order to reduce the Q-factor in the higher-order mode RDRA. A design was developed and subsequently simulated using Ansoft HFSS ver 16.0 by utilizing Duroid 5880 dielectric substrate with a thickness (ts) of 0.254 mm, a permittivity (εs) of 2.2 and a loss tangent (δ) of 0.001 at 15 GHz. The higher-order mode, 〖〖TE〗^y〗_1δ3 RDRA achieved the measured gain at 9.76 dBi and the measured impedance bandwidth as much 2.5 GHz which is 4.7% more compared to the fundamental mode, 〖〖TE〗^y〗_1δ1. The result should be considered suitable for 5G applications.
Mutual Coupling Reduction between Asymmetric Reflectarray Resonant Elements IJECEIAES
A physically asymmetric reflectarray element has been proposed for wide band operations. The dual resonant response has been introduced by tilting one side of the square path element. The numerical results have been analyzed in the frequency band between 24GHz to 28GHz where a reflection phase range of more than 600° has been achieved. The proposed asymmetric element can produce mutual coupling with adjacent elements on a reflectarray. This effect has been monitored by placing the elements in a mirror configuration on the surface of reflectarray. The single unit cell element results have been compared with conventional 4 element unit cell and proposed mirroring element configuration. The proposed mirroring element technique can be used to design a broadband reflectarray for high gain applications.
21 15036 design of planar dielectric resonator antenna array at 28 g hz(edit)nooriasukmaningtyas
This article presents a planar array of rectangular Dielectric Resonator Antenna operating for 28 GHz applications. The proposed antenna is formed through two stages of designs which are a single element and planar array. It is made up from a ceramic material with a dielectric constant of 10 and mounted on RT/Duroid 5880 with a relative permittivity of 2.2 and a thickness of 0.254 mm. A prospective study using three different configurations of three by three planar array is done in order to obtain the best performance in terms of bandwidth, gain, and cost reduction. Besides that, this study is also conducted for a beam steering capability of each configuration. Finally, the best configuration is proposed for 5G application.
Numerical parametric study on interval shift variation in simo sstd technique...eSAT Journals
Abstract SSTD (Single Station Time Domain) technique is one of the efficient methods used to extract modal parameters of a structure. Instead of extracting the parameters in frequency domain by utilising Fast Fourier Transform (FFT) as used by some other methods, this technique only relies on free decay responses to obtain the required parameters. In this paper, a parametric study on time shift interval on algorithm method is investigated. The accuracy assessment is made using simulated analytical data with known properties where percentage error between the results of simulated and this method can be calculated and compared. Keywords: SSTD (Single Station Time Domain), FFT, EMA
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Abstract
Terahertz sub-surface imaging offers an effective solution for surface and 3D imaging because of minimal
sample preparation requirements and its ability to “see” below the surface. Another important property is the ability
to inspect on a layer-by layer basis via a non-contact route, non-destructive route. Terahertz 3D imager designed
at Applied Research and Photonics (Harrisburg, PA) has been used to demonstrate reconstructive imaging with a
resolution of less than a nanometer. Gridding with inverse distance to power equations has been described for 3D
image formation. A continuous wave terahertz source derived from dendrimer dipole excitation has been used for
reflection mode scanning in the three orthogonal directions. Both 2D and 3D images are generated for the analysis
of silver iodide quantum dots’ size parameter. Layer by layer image analysis has been outlined. Graphical analysis
was used for particle size and layer thickness determinations. The demonstrated results of quantum dot particle
size checks well with those determined by TEM micrograph and powder X-ray diffraction analysis. The reported
non-contact measurement system is expected to be useful for characterizing 2D and 3D naomaterials as well as for process development and/or quality inspection at the production line.
Preparation and characterization of nimesulide loaded cellulose acetate hydro...Jing Zang
The aim of this study is to prepare nimesulide loaded cellulose acetate hydrogen phthalate nanoparticles by salting out technique. In this study Cellulose acetate Hydrogen phthalate was taken as polymer. Nimesulide was selected as a model drug. This technique is suitable for drugs and polymers that are soluble in polar solvents such as acetone or ethanol. The effect of drug concentration and polymer concentration on nanoparticle size, shape, uniform size distribution and stability was studied. Nanoparticles were evaluated for particle size, zetapotential and particle size distribution. Size of the particle was measured by SEM.(Scanning electron microscope).Surface charge and stability of the resultant nanoparticles was determined by Zetasizer. Particle size distribution was determined by Photon Correlation Spectroscopy (PCS) with a Malvern Zetasizer Nano-ZS. The cellulose acetate hydrogen phthalate concentration and nimesulide concentration was varied from 5mg/ml to 10 mg/ml. The effect of drug and polymer concentrations on nanoparticle size, shape, particle size distribution was studied. Increased drug concentration has no impact on the particle size. The size of the particle was found to be decreased with increased polymer concentration. Increased polymer concentration has resulted in uniform particle size distribution. Higher the polymer concentrations and lower the drug concentrations resulted in uniform particle size distribution.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Design of Symmetric dispersion compensated, long haul, Single and Multichanne...IOSR Journals
Abstract: Here we propose a model on Enhanced- Large Effective Area Fiber (E-LEAF) and Dispersion Compensation Module (DCM) with precise designed Dispersion Compensation Fiber (DCF). The Model is implemented in a long haul Single and Multichannel Optical telecommunication systems with E-LEAF as data transmission Fiber (NZ-DSF) of 1700Km (85 Km SMF×20 loops) length. The DCM is proposed in Symmetric Compensation fashion consisting of 20Km (2Km×20spans) length DCF in Pre-Compensation and Post-Compensation totally comprising of 40Km length DCF for complete Compensation of total Optical Link. Thereby, we study the effect of various Line Coding Schemes like NRZ, RZ, CS-RZ, DUOBINARY and MODIFIED DUOBINARY in single and multichannel optical link with our designed DCM and concluded the suitable line coding scheme for our proposed model. This paper focus on the theoretical background, design procedures, technical terms and finally a simulation model is experimented with proposed parameters to realize the foresaid concepts with various modulation formats.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Comparison of PMD Compensation in WDM SystemsIOSR Journals
The need for larger capacities in long haul optical digital transmission lead to greater channel
density which can be achieved by wavelength division multiplexing and increasing the bit rate of each channel.
As data rates increases, certain phenomena such as dispersion began to show up as obstacles. At higher bit
rates beyond 2.5Gbps polarization mode dispersion (PMD) becomes a main factor in the degradation of the
transmission characteristics. PMD occurs when slightly different planes of light inside a fiber travel at slightly
different speeds and make it impossible to transmit data reliably at high speed in single mode fibers. PMD is
caused due to optical birefringence in the fiber due to which the two modes within a single mode fiber travel
with different group velocities and the random change of this birefringence along the fiber length results in
random coupling between the modes. This effect of PMD results in broadening of transmitted pulses that limit
the transmission capacity of the fiber. In high-speed optical communication systems working at data rates of
10Gbps and beyond, signal distortion caused by PMD is also a major limitation of the transmission distance.
This paper intends to analyze the performance of PMD compensation by optical compensation technique and
using DCF in a two channel WDM system. The analysis is done through eye diagrams from which the Q value
and bit error rate can be determined by simulating with OptSim5.3, which includes the latest simulation
algorithms to guarantee the highest possible accuracy and real world results
16 15032 hight order ijeecs 1570310229 (manuscript)(edit)nooriasukmaningtyas
The excitation of the higher-order mode, 〖〖TE〗^y〗_1δ3 in rectangular dielectric resonator designed was explored to enhance the antenna gain and detailed elaboration is presented in this paper. The antenna was fed by a 50Ω microstrip line through an aperture cut in the ground plane. Besides avoiding spurious radiation, this feeding technique gives flexibility in controlling the amount of coupling in order to reduce the Q-factor in the higher-order mode RDRA. A design was developed and subsequently simulated using Ansoft HFSS ver 16.0 by utilizing Duroid 5880 dielectric substrate with a thickness (ts) of 0.254 mm, a permittivity (εs) of 2.2 and a loss tangent (δ) of 0.001 at 15 GHz. The higher-order mode, 〖〖TE〗^y〗_1δ3 RDRA achieved the measured gain at 9.76 dBi and the measured impedance bandwidth as much 2.5 GHz which is 4.7% more compared to the fundamental mode, 〖〖TE〗^y〗_1δ1. The result should be considered suitable for 5G applications.
Mutual Coupling Reduction between Asymmetric Reflectarray Resonant Elements IJECEIAES
A physically asymmetric reflectarray element has been proposed for wide band operations. The dual resonant response has been introduced by tilting one side of the square path element. The numerical results have been analyzed in the frequency band between 24GHz to 28GHz where a reflection phase range of more than 600° has been achieved. The proposed asymmetric element can produce mutual coupling with adjacent elements on a reflectarray. This effect has been monitored by placing the elements in a mirror configuration on the surface of reflectarray. The single unit cell element results have been compared with conventional 4 element unit cell and proposed mirroring element configuration. The proposed mirroring element technique can be used to design a broadband reflectarray for high gain applications.
COLOUR IMAGE REPRESENTION OF MULTISPECTRAL IMAGE FUSION acijjournal
ABSTRACT
The availability of imaging sensors operating in multiple spectral bands has led to the requirement of image fusion algorithms that would combine the image from these sensors in an efficient way to give an image that is more perceptible to human eye. Multispectral Image fusion is the process of combining images optically acquired in more than one spectral band. In this paper, we present a pixel-level image fusion that combines four images from four different spectral bands namely near infrared(0.76-0.90um), mid infrared(1.55-1.75um),thermal- infrared(10.4-12.5um) and mid infrared(2.08-2.35um) to give a composite colour image. The work coalesces a fusion technique that involves linear transformation based on Cholesky decomposition of the covariance matrix of source data that converts multispectral source images which are in grayscale into colour image. This work is composed of different segments that includes estimation of covariance matrix of images, cholesky decomposition and transformation ones. Finally, the fused colour image is compared with the fused image obtained by PCA transformation.
COLOUR IMAGE REPRESENTION OF MULTISPECTRAL IMAGE FUSIONacijjournal
The availability of imaging sensors operating in multiple spectral bands has led to the requirement of
image fusion algorithms that would combine the image from these sensors in an efficient way to give an
image that is more perceptible to human eye. Multispectral Image fusion is the process of combining
images optically acquired in more than one spectral band. In this paper, we present a pixel-level image
fusion that combines four images from four different spectral bands namely near infrared(0.76-0.90um),
mid infrared(1.55-1.75um),thermal- infrared(10.4-12.5um) and mid infrared(2.08-2.35um) to give a
composite colour image. The work coalesces a fusion technique that involves linear transformation based
on Cholesky decomposition of the covariance matrix of source data that converts multispectral source
images which are in grayscale into colour image. This work is composed of different segments that
includes estimation of covariance matrix of images, cholesky decomposition and transformation ones.
Finally, the fused colour image is compared with the fused image obtained by PCA transformation.
Analysis of Adaptive and Advanced Speckle Filters on SAR DataIOSRjournaljce
Synthetic Aperture RADAR(SAR) images get inherently affected by speckle noise which is multiplicative in nature. This noise affects the image spatial statistics and properties. Over the past several years, many SAR denoising algorithms have been developed to reduce speckle noise. Some of the standard speckle filters are Gamma MAP, Lee, Frost and Kuan filters. Further, these have also been modified to obtain better results after filtering, than their original counterparts. Apart from the standard speckle filters, advanced SAR filters like Block Matching 3 Dimensional (BM3D) are also present. In this paper several standard as well as advanced speckle filters have been analyzed and compared. For comparison, Quality Assessment has been performed where the filtered images are compared to each other using parameters like Radiometric Resolution and others. These parameters help to distinguish the performance of the filters on basis of signal strength, speckle reduction, mean preservation and edge and feature preservation. In the paper, radiometric resolution, speckle index and mean preservation index will be used to analyze among the performance of the filters.
Study the effect of thin film thickness on the optical features of (IR5 laser...TELKOMNIKA JOURNAL
The linear optical features such as (transmittance T, absorbance A, the effective length 퐿푒푓푓, absorption coefficient 훼 and refractive index 푛 ) for the thin films samples of (3x10-3 mol/l of (IR5) laser dye, 0.02 gm of (CdS) nanoparticles and 0.04 gm of pp polymer) had been studied at different values of film thickness in one time and at different number of Yb:GdVO4 laser pulses. The non-linear optical features in terms of transmittance difference Δ푇푝−푣, non-linear refractive index 푛2, non–linear phase shift Δ훷표 non-linear absorption coefficient 훽 and minimum normalized transmittance 푇(푍) have been computed in relation to obtained normalized transmittance data from setup of Z-scan with open and closed apertures, calculated for (3x10-3 mol/l of (IR5) laser dye, 0.02 gm of (CdSe) nanoparticles and 0.04 gm of (pp) polymer) thin films at different values of film thickness at in one time and at different Yb:GdVO4 laser pulses. Thick films causes in deleting the non-linear effects generated by different layers. The (CdSe) nanoparticles leads to an absorption shifting of the wavelengths to lengthier wavelengths of red shift. So, this can be used in selecting the nanoparticles and medium with applicable exciting wavelengths. The film thickness and the laser pulses have the main effects in consolidating the Non-linear optical features.
Atmospheric Correction of Remotely Sensed Images in Spatial and Transform DomainCSCJournals
Remotely sensed data is an effective source of information for monitoring changes in land use and land cover. However remotely sensed images are often degraded due to atmospheric effects or physical limitations. Atmospheric correction minimizes or removes the atmospheric influences that are added to the pure signal of target and to extract more accurate information. The atmospheric correction is often considered critical pre-processing step to achieve full spectral information from every pixel especially with hyperspectral and multispectral data. In this paper, multispectral atmospheric correction approaches that require no ancillary data are presented in spatial domain and transform domain. We propose atmospheric correction using linear regression model based on the wavelet transform and Fourier transform. They are tested on Landsat image consisting of 7 multispectral bands and their performance is evaluated using visual and statistical measures. The application of the atmospheric correction methods for vegetation analyses using Normalized Difference Vegetation Index is also presented in this paper.
Characterization of the Scattering Properties of a Spherical Silver Nanoparti...AI Publications
Within this work Lumerical FDTD is applied to simulate how plane polarized light interacts with a single spherical silver nanoparticle. It allows for the determination of the light retention capability of the particle based upon counting how much light is scattered away from the particle after a long period as compared to how much enters the simulation region. This quantity, the nanoparticle albedo, is a key parameter in relating the scattering enhanced out-coupling efficiency. The two-dimensional finite-difference time-domain (FDTD) simulations are described for scattering layers with spherical nanoparticles in various external media for non-dispersive and have external indices from 1.0 to 2.0. FDTD takes into account this dispersive nature of the refractive index, which analytical solutions do not. A comparison between these two results will indicate that they agree within expected errors. The scattering and absorption cross-sections (CScat and CAbs), scattering and absorption efficiencies (QScat and QAbs), and albedo are calculated from this data. The albedo values are then output to the isotropic scattering model and an expected out-coupling factor is determined.
Separability Analysis of Integrated Spaceborne Radar and Optical Data: Sudan ...rsmahabir
Abstract-The purpose of this study was to determine via spectral separability using divergence measures the best individual and combinations of various numbers of bands for five land cover/ land use classes along the Blue Nile in Sudan. The data for this analysis were a stack of 15 layers including RADARSAT-2 C-band and PALSAR L-band quad-polarized radar registered with ASTER optical data, as well as four variance texture measures extracted from the RADARSAT-2 images. Spectral signatures were obtained for each class and examined by various separability measures. This examination is useful for better understanding the relative value of different types of remote sensing data and best band combinations for possible visual analysis and for improving land cover/ land use classification accuracy. Results show that the best single band for analysis was the RADARSAT-2 VH variance texture measure. The best pair of bands was the ASTER visible red and the RADARSAT-2 HV variance texture, which also included the PALSAR VH band for the best three band combination, all bands being very different data types. Further, based upon the divergence values, only eight bands are needed to achieve maximum separation between land cover/ land use classes. Beyond this point, classification accuracy is expected to decrease, with as few as six bands needed to reach viable classification accuracy.
IMPROVEMENT OF BM3D ALGORITHM AND EMPLOYMENT TO SATELLITE AND CFA IMAGES DENO...ijistjournal
This paper proposes a new procedure in order to improve the performance of block matching and 3-D filtering (BM3D) image denoising algorithm. It is demonstrated that it is possible to achieve a better performance than that of BM3D algorithm in a variety of noise levels. This method changes BM3D algorithm parameter values according to noise level, removes prefiltering, which is used in high noise level; therefore Peak Signal-to-Noise Ratio (PSNR) and visual quality get improved, and BM3D complexities and processing time are reduced. This improved BM3D algorithm is extended and used to denoise satellite and color filter array (CFA) images. Output results show that the performance has upgraded in comparison with current methods of denoising satellite and CFA images. In this regard this algorithm is compared with Adaptive PCA algorithm, that has led to superior performance for denoising CFA images, on the subject of PSNR and visual quality. Also the processing time has decreased significantly.
IMPROVEMENT OF BM3D ALGORITHM AND EMPLOYMENT TO SATELLITE AND CFA IMAGES DENO...ijistjournal
This paper proposes a new procedure in order to improve the performance of block matching and 3-D filtering (BM3D) image denoising algorithm. It is demonstrated that it is possible to achieve a better performance than that of BM3D algorithm in a variety of noise levels. This method changes BM3D algorithm parameter values according to noise level, removes prefiltering, which is used in high noise level; therefore Peak Signal-to-Noise Ratio (PSNR) and visual quality get improved, and BM3D complexities and processing time are reduced. This improved BM3D algorithm is extended and used to denoise satellite and color filter array (CFA) images. Output results show that the performance has upgraded in comparison with current methods of denoising satellite and CFA images. In this regard this algorithm is compared with Adaptive PCA algorithm, that has led to superior performance for denoising CFA images, on the subject of PSNR and visual quality. Also the processing time has decreased significantly.
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.
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.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
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it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
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A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
1. JUNE 25, 2012
TOPIC:
BAND
COMBINATIONAN
Submitted To:
D BAND RATIOS
Sir Amir Mehmood
AND PRINCIPLE
Subject:
COMPONENT
Remote Sensing II
ANALYSIS (PCA)
Group: Girls_lll
Members:
Roll No’s
Atiqa Ijaz Khan
03
Rafia Naheed
09
Syeda Rbiya Mahmood
Rabia Zahoor
14
28
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2. JUNE 25, 2012
Table of contents
Band Ratios ........................................................................................................................................... 03
Definitions ......................................................................................................................................... 03
Formula ............................................................................................................................................. 03
Advantage………………………………………………………………………………………………………………………………… 03
Band Combination................................................................................................................................ 07
Principal Component Analysis ............................................................................................................. 09
History ........................................................................................................................................... 09
Objective…………………………………………………………………………………………………………………………………09
Definitions……………………………………………………………………………………………………………………………… 09
Mathematical Analysis…………………………………………………………………………………………………………… 10
Important Terms in PCA………………………………………………………………………………………………………… 10
Outline of PCA………………………………………………………………………………………………………………………. 12
Advantages……………………………………………………………………………………………………………………………..13
Disadvantages…………………………………………………………………………………………………………………………13
Summary…………………………………………………………………………………………………………………………………13
Expert Opinion………………………………………………………………………………………………………………………..14
References............................................................................................................................................15
2
3. JUNE 25, 2012
Band ratios
Definitions:
“Band rationing means dividing the pixels in one band by the corresponding pixels in a
second band.”
“Ratio images are enhancements resulting from the division of DN values in one spectral
band by the corresponding values in another band.”
“To generate a band ratio image, the high digital reflectance values of a specific material is
divided by the corresponding digital reflectance value with lowest reflectance.”
The reason for this is twofold:
1. One is that differences between the spectral reflectance curves of surface types can be
brought out.
2. The second is that illumination, and consequently radiance, may vary, the ratio
between an illuminated and a not illuminated area of the same surface type will be the
same.
Formula for Number of Possible Ratios:
The number of possible ratios that can be developed from n bands of data is:
“n (n-1)”
Example:
For the 6 non-thermal bands of the Landsat Tm or ETM+ data there are 6(6-1), or 30
possible combinations (15 original and 15 reciprocal).
Example on Vegetation:
The near-infrared-to-red for healthy vegetation is normally very high. That for stressed
vegetation is typically lowers (a near-infrared reflectance decrease and the red reflectance
increases). The near-infrared-to-red (red-to-near-infrared) rationed image might be useful
for differentiating between areas of the stressed and non-stressed vegetation. This type of
ratio has been employed extensively in vegetation indices aimed at qualifying greenness
and biomass.
Advantage:
1. The major advantage of ratio images is that they convey the spectral or color
characteristics of the image features, regardless of variations in the scene illumination
conditions.
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4. JUNE 25, 2012
2. Rationed images are often useful for discriminating refined spectral variation in a
scene that are masked by the brightness variations in images from the spectral bands
or in standard color composite.
Which bands to ratio?
The answer depends on the purpose for creating the ratio. There is a physical basis why each
of the different band combinations works, but it is partially a trial and error process. These
sorts of band ratios come in a couple of different “flavors”.
ETM+ For an Example:
Landsat images are composed of seven different bands, each representing a different portion
of the electromagnetic spectrum. In order to work with Landsat band combinations (RGB
composites of three bands) first we must understand the specifications of each band.
Band 1: (0.45-0.52 µm, blue-green)
This short wavelength of light penetrates better than the other bands, and it is often the band
of choice for monitoring aquatic ecosystems (mapping sediment in water, coral reef habitats,
etc.). Unfortunately this is the “noisiest” of the Landsat bands since it is most susceptible to
atmospheric scatter.
Band 2: (0.52-0.60 µm, green)
This has similar qualities to band 1 but not as extreme. The band was selected because it
matches the wavelength for the green we see when looking at vegetation.
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5. JUNE 25, 2012
Band 3: (0.63-0.69 µm, red)
Since vegetation absorbs nearly all red light (it is sometimes called the chlorophyll absorption
band) this band can be useful for distinguishing between vegetation and soil and in
monitoring vegetation health.
Band 4: (0.76-0.90 µm, near infrared)
Since water absorbs nearly all light at this wavelength water bodies appear very dark. This
contrasts with bright reflectance for soil and vegetation so it is a good band for defining the
water/land interface.
Band 5: (1.55-1.75 µm, mid-infrared)
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6. JUNE 25, 2012
This band is very sensitive to moisture and is therefore used to monitor vegetation and soil
moisture. It is also good at differentiating between clouds and snow.
Band 6: (10.40-12.50 µm, thermal infrared)
This is a thermal band, which means it can be used to measure surface temperature. Band 6 is
primarily used for geological applications but it is sometime used to measure plant heat
stress. This is also used to differentiate clouds from bright soils as clouds tend to be very
cold. The resolution of band 6 (60m) is half of the other bands.
Band 7: (2.08-2.35 µm mid-infrared)
This band is also used for vegetation moisture although generally band 5 is preferred for that
application, as well as for soil and geology mapping.
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7. JUNE 25, 2012
Band combination
Introduction:
Effective display of an image is critical for effective practice of remote sensing. Band
combination is the term that remote sensing use to refer to the assignment of the colors to
represent brightness in different regions of spectrum. A key constraint for the display of any
multispectral image is that human vision portrays differences in the color of surfaces through
our eyes ability to detect differences in brightness in three additives primary-blue, green, red.
Need of Band Combinations:
Single band remote sensing image may not be sufficient top extract desire information,
handling of multiple bands is also inconvenient. Multiple bands may be combined to generate
one or more transformed combined bands following different mathematical operations.
Multiple bands combination has the capability to enhance the features of the interest of the
analyst. Band combination includes addition, subtraction, and rationing, principal component
analysis and so on.
Mathematical treatment:
Band combination is general a combination of multi band (e.g. multispectral) images. It is
defined as an output of multiband functions or operations. In a normal band combination, the
same operation is carried out on each pixel in the image. The output of the operation is an
image of new pixel generated due to some mathematical combination of pixel values of
various bands of an input image.
ETM+ For an Example:
Common Landsat Band Combinations Individual bands can be composited in a Red, Green,
and Blue (RGB) combination in order to visualize the data in color. There are many different
combinations that can be made, and each has their own advantages and disadvantages. Here
are some commonly used Landsat RGB band combinations (color composites):
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8. JUNE 25, 2012
3, 2, 1 RGB: This color composite is as close to true color that we can get with a Landsat
ETM image. It is also useful for studying aquatic habitats. The downside of this set of bands
is that they tend to produce a hazy image.
4, 3, 2, RGB: This has similar qualities to the image with bands 3, 2, 1 however, since this
includes the near infrared channel (band 4) land water boundaries are clearer and different
types of vegetation are more apparent. This was a popular band combination for Landsat
MSS data since that did not have a mid-infrared band.
4, 5, 3 RGB: This is crisper than the previous two images because the two shortest
wavelength bands (bands 1 and 2) are not included. Different vegetation types can be more
clearly defined and the land/water interface is very clear. Variations in moisture content are
evident with this set of bands. This is probably the most common band combination for
Landsat imagery.
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9. JUNE 25, 2012
7, 4, 2 RGB: This has similar properties to the 4, 5, and 3 band combination with the biggest
difference being that vegetation is green. This is the band combination that was selected for
the global Landsat mosaic created for NASA.
5, 4, 1 RGB: This band combination has similar properties to the 7, 4, and 2 combination,
however it is better suited in visualizing agricultural vegetation.
Principal Component Analysis (PCA)
History:
Principal component analysis was first proposed in 1933 by Hotelling in order to solve the
problem of decor relating the statistical dependency between variables in multi-variety
statistical data derived from exam scores, Hotelling (1933). Since then, PCA has become a
widely used tool in statistical analysis for the measurement of correlated data relationships
between variables, but it has also found applications in signal processing and pattern
recognition for which it is often referred to as the Karhunen-Loeve transform, Therein
(1989).
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10. JUNE 25, 2012
Objectives of Principal Component Analysis:
1. To discover or to reduce the dimensionality of the data set.
2. To identify new meaningful underlying variables.
Definition of Principal Components Analysis (PCA):
“Is a method in which original data is transformed into a new coordinate system, which acts
to condense the information, which is found in the original inter-correlated variables into a
few uncorrelated variables, called principal components”
“In any principal components rotation, the first component or dimension accounts for the
maximum proportion of the variance of the original image, and subsequent components
account for maximum proportion of the remaining variance.”
Mathematical background on principal component analysis:
Eigen Analysis:
The mathematical technique used in PCA is called Eigen analysis:
Solve for the eigenvalues and eigenvectors of a square symmetric matrix with sums of
squares and cross products. The eigenvector associated with the largest eigenvalue has the
same direction as the first principal component. The eigenvector associated with the second
largest eigenvalue determines the direction of the second principal component. The sum of
the eigenvalues equals the trace of the square matrix and the maximum number of
eigenvectors equals the number of rows (or columns) of this matrix.
Important Terms in Principle Component Analysis (PCA):
1. Factor analysis: The search for the “factors” (i.e. band combinations) that contain the
most information.
2. Original Data: The set of brightness values for n bands and m pixels.
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11. JUNE 25, 2012
3. PCA: A linear method of factor analysis that uses the mathematical concepts of
eigenvalues and eigenvectors. It amounts to a “rotation” of the coordinate axes to identify the
Principle Components.
4. Principle Component: An optimum linear combination of band values comprising a new
data layer (or image).
5. Co-variance: A measure of the redundancy of two bands (i and j), created by summing the
product of the two band values over all the pixels (M).
6. Correlation: Co-variance normalized by the variances of the two bands.
7. Redundant bands: Bands with a CC=1 contain the same information.
8. Correlation Matrix: A square symmetric matrix containing the correlation coefficients
between every pair of bands. It contains statistical information about the data.
9. Eigenvector: The set of weights applied to band values to obtain the PC. Eigenvectors
represent the orientation of the principal axes of each component (as an angle). Eigenvectors
are standardized so that the squares of the elements sum to one. Therefore, an eigenvector
loading reflects the relative importance of a variable within a principal component but does
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12. JUNE 25, 2012
not reflect the value of the component itself. Eigen Vectors show the direction of axes of a
fitted ellipsoid
10. Eigenvalue: A measure of the variance in a PC. Eigenvalues represent the lengths of each
successive component axis, therefore the greater the eigenvalues the more "important" the
component is for explaining the variation in the dataset. The percentage of the total variance
explained by each eigenvalue is often more useful as it gives the relative contribution of each
eigenvalue to explaining the variance in the dataset. Eigen Values show the significance of
the corresponding axis. The larger the Eigen value, the more separation between mapped
data. For high dimensional data, only few of Eigen values are significant.
11. Axes Rotation: Multiplying the original data matrix by a matrix of eigenvectors is
equivalent to rotating the data to a new coordinate system.
12. Standraised PC: The principal components calculated using correlation matrix.
13. Unstandardized PC: The principal components calculated using covariance matrix.
Outline of Principle Component Analysis:
1. Start with an image data set including the reflectance values from n bands with m pixels.
This non-square nxm matrix will be called D.
2. This data set may contain “redundancies” i.e. bands whose reflectance’s correlate
perfectly with another band. It may also contain noise.
Noise: Our definition of noise is signal that does not correlate at all between bands
3. Subtract the means from each band and compute the variances and co-variances between
each pair of bands. Place these values into an nxn square matrix (say A). It is symmetric.
Normalize the co-variances by the square-root of the variances to form the correlation matrix.
This is a useful matrix to study, and it forms the basis of PCA.
Note: At this point, one could just delete bands that correlate well with other bands. This
action would reduce the size of the data set. The PCA method below is more objective and
systematic.
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13. JUNE 25, 2012
4.
Find
formula:
the
eigenvalues
and
eigenvectors
of
the
dataset
by
solving
this
________________________ (1)
Where λ is an eigenvalue and V is an eigenvector.
Eigen: The word “Eigen” means that these quantities are characteristics of the correlation
matrix (say A).They reveal the hidden properties it.
Typically there will be n different solutions to (1), so there will be n paired eigenvalues and
eigenvectors (i.e. iλ .and IV). The eigenvalues will be real and positive (because A is
symmetric). We usually list these eigenvalues and eigenvectors in order of decreasing
eigenvalue. That is, the first eigenvector corresponds to the largest eigenvalue.
5. The eigenvectors have a dimension equal to n, i.e. the number of original bands. The first
eigenvector represents a synthetic spectrum containing the largest variance across the scene.
6. The eigenvectors are orthogonal to each other, for example 021 =VV.
They are normally scaled so that their length is unity, that is 1|| =iV.
With these two properties, the multiplying the original dataset by an eigenvector rotates the
reflectance vector for a pixel where PC1 is the first Principle Component. It is a vector with
m components representing a brightness value for each pixel, i.e. it is a new single band
image. Its pixel values are linear combinations of the original band values for that pixel. The
weights are given by the components of the first eigenvector. Because of our ordering of
eigenvalues, this image contains the most “information” of any single image.
The first eigenvalue is proportional to the brightness variance in the first PC.
To obtain the other Principle Components, we repeat (2) with the other eigenvectors so that
___________________ (2)
And the PC data layers can be stacked to form a new “data cube”. If desired, only the first
few PCs can be kept, reducing the size of the dataset. For example, if the original dataset had
200 bands (i.e. n = 200), you could keep only the ten PCs with the largest eigenvalues. This
dataset is only 1/20 of the original size. The number of pixels is unchanged.
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14. JUNE 25, 2012
7. A remarkable property of the new data cube is that the band values are completely
uncorrelated. There is no more redundancy! (Actually, the uncorrelated data in the original
scene is pushed off into the high PC components.) Another property is that the bands are
ordered by their “information content” (i.e. variance).
Advantage:
The primary advantage of PCA is Principal Component’s analysis generates orthogonal
(uncorrelated) components that represent 100% of the variance present in the original dataset.
Disadvantage:
A disadvantage of the PC representation is that one can no longer identify spectral signatures
of objects. A “pixel profile” in the new data cube is not a spectral signature (i.e. reflectance
plotted against wavelength).
Summary of Principal Components Analysis (PCA):
PCA is a technique that transforms the original vector image data into smaller set of
uncorrelated variables.
The variables represent most of the image information and easier to interpret.
Principal components are derived such that the first PC accounts for much of the
variation of the original data. The second (vertical) accounts for most of the remaining
variation.
PCA is useful in reducing the dimensionality (number of bands) that used for analysis.
Minimum noise fraction (MNF) method can be used with hyper spectral data for noise
reduction.
Expert Opinion about PCA:
1. Mather, (2003) states that PCA is a standard method for deriving reduced data
or minimizing information redundancy in the original image.
2. Zumsprekel and Prinz, (2000) states that PCA reduces the dimensionality
Of the dataset while retaining as much information as possible.
3. A more detailed reading of PCA can be taken from Jensen (1996), Mather
(2003), and Gibson and Power (2000). Principal Component Analysis was run on bands
1, 2, 3, 4, 5, &7. The results were six PCA bands and were visually assessed using
RGB band combinations.
4. Zumsprekel and Prinz, (2000) and Rajesh (2008) state that the first PC (PC
-1) combines the total albedo difference of all original TM bands, the second PC (PC-2)
emphasize the spectral differences between the visible spectrum (VIS) and the infrared
spectrum (IR) and the third PC (PC-3) illustrates albedo variations within the IR
spectrum. They further state that the higher principal components (PC-4 to -6) may
contain important lithological information but are often increasingly loaded with noise
effect. The first 3 PC bands have been selected in this study, because they best highlight the
lithological features.
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15. JUNE 25, 2012
References
PDF-FORMATS :
1. A HYBRID IMAGE CLASSIFICATION APPROACH FOR THE SYSTEMATIC
ANALYSIS OF LAND COVER (LC) CHANGES IN THE NIGER DELTA
REGION.
2. A TUTORIAL ON PRINCIPAL COMPONENT ANALYSIS.
3. EVALUATING PRINCIPAL COMPONENTS ANALYSIS FOR IDENTIFYING
OPTIMAL BANDS USING WETLAND HYPERSPECTRAL MEASUREMENTS
FROM THE GREAT LAKES, USA ,
4. IDENTIFYING HYDROCARBON LEAKAGE INDUCED ANOMALIES USING
LANDSAT-7 /ETM+ DATA PROCESSING TECHNIQUES IN THE WEST SLOPE
OF SONGLIAO BASIN, CHINA
5. LAND-COVER
CLASSIFICATION
USING
ASTER
MULTI-BAND
COMBINATIONS BASED ON WAVELET FUSION AND SOM NEURAL
NETWORK
BOOKS:
1. DIGITAL REMOTE SENSING BY PRITHVISH NAG, M. KUDRAT
2. INTRODUCTION TO
RANDOLPH WYNNE
3.
REMOTE
SENSING, BY
JAMES
CAMPBELL,
JENSEN, J.R. (1996). INTRODUCTORY DIGITAL IMAGE PROCESSING: A
REMOTE SENSING PERSPECTIVE. SECOND EDITION. PRENTICE HALL.
4. LILLESAND, T. M. AND R. W. KIEFER (2002). REMOTE SENSING AND
IMAGE INTERPRETATION. NEW YORK, JOHN WILEY & SONS, FIFTH
EDITION.
5. TEXTBOOK
OF
REMOTE
SENSING
AND
INFORMATION SYSTEM BY KALI CHARAN SAHU
GEOGRAPHICAL
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