Image processing ppt

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Image processing ppt

  1. 1. Presented & performed by Arunachalam. PL Nagaraj.K.N COMPUTER ENGINEERING
  2. 2. • INTRODUCTION• ACQUIRING IMAGES – HUMAN RELIANCE ON IMAGES FOR INFORMATION – ELECTRONICS AND BANDWIDTH LIMITATIONS – HIGH RESOLUTION IMAGING – COLOR IMAGING – COLOR SPACES – COLOR DISPLAYS – IMAGE TYPES• ITS TIME FOR DEMO• CONCLUSION• BIBLIOGRAPHY
  3. 3. Image processing involves processing oraltering an existing image in a desiredmanner.The next step is obtaining an image in areadable format.The Internet and other sources providecountless images in standard formats.
  4. 4. Image processing are of two aspects..improving the visual appearance ofimages to a human viewerpreparing images for measurement ofthe features and structures present.
  5. 5. Since the digital image is “invisible” it must beprepared for viewing on one or more output device(laser printer,monitor,etc)The digital image can be optimized for the applicationby enhancing or altering the appearance of structureswithin it (based on: body part, diagnostic task,viewing preferences,etc)It might be possible to analyze the image in thecomputer and provide cues to the radiologists to helpdetect important/suspicious structures (e.g.:Computed Aided Diagnosis, CAD)
  6. 6. Scientific instruments commonly produceimages to communicate results to theoperator, rather than generating an audibletone or emitting a smell.Space missions to other planets and CometHalley always include cameras as majorcomponents, and we judge the success of thosemissions by the quality of the images returned.
  7. 7. Image-to-image transformationsImage-to-information transformationsInformation-to-image transformations
  8. 8. Enhancement (make image more useful, pleasing)Restoration Egg. deblurring ,grid line removalGeometry (scaling, sizing , Zooming, Morphing one object to another).
  9. 9. Image statistics (histograms) Histogram is the fundamental tool for analysis and image processingImage compressionImage analysis (image segmentation, featureextraction, pattern recognition)computer-aided detection and diagnosis (CAD)
  10. 10. Decompression of compressed image data.Reconstruction of image slices from CT or MRIraw data.Computer graphics, animations and virtual reality(synthetic objects).
  11. 11. The process of obtaining an high resolution (HR)image or a sequence of HR images from a set oflow resolution (LR) observations.HR techniques are being applied to a variety offields, such as obtaining improved still images high definition television, high performance color liquid crystal display (LCD) screens, video surveillance, remote sensing, and medical imaging.
  12. 12. Conversion from RGB (the brightness of the individualred, green, and blue signals at defined wavelengths) toYIQ/YUV and to the other color encoding schemes isstraightforward and loses no information. Y, the “luminance” signal, is just the brightness of apanchromatic monochrome image that would be displayedby a black-and-white television receiver
  13. 13. • Most computers use color monitors that have much higher resolution than a television set but operate on essentially the same principle.• Smaller phosphor dots, a higher frequency scan, and a single progressive scan (rather than interlace) produce much greater sharpness and color purity.
  14. 14. Digital processing requires images to be obtained in theform of electrical signals. These signals can be digitized intosequences of numbers which then can be processed by acomputer. There are many ways to convert images intodigital numbers. Here, we will focus on video technology, asit is the most common and affordable approach.
  15. 15. • Multiple images may constitute a series of views of the same area, using different wavelengths of light or other signals.• Examples include the images produced by satellites, such as – the various visible and infrared wavelengths recorded by the Landsat Thematic Mapper(TM), and – images from the Scanning Electron Microscope (SEM) in which as many as a dozen different elements may be represented by their X-ray intensities.• These images may each require processing.
  16. 16. A general-purpose computer to be useful for imageprocessing, four key demands must be met: high-resolution image display, sufficient memory transferbandwidth, sufficient storage space, and sufficientcomputing power.A 32-bit computer can addressup to 4GB of memory(RAM).
  17. 17. • Adobe Photoshop• Corel Draw• Serif Photoplus
  18. 18. In electrical engineering and computer science, imageprocessing is any form of signal processing for which theinput is an image, such as photographs or frames of video;the output of image processing can be either an image or aset of characteristics or parameters related to the image.Most image-processing techniques involve treating theimage as a two-dimensional signal and applying standardsignal-processing techniques to it.
  19. 19. Create Apply Apply Knowledge Knowledge Knowledge Seminar - Knowledge SharingAssimilateAssimilate And Structure StructureKnowledgeKnowledge Acquiring Knowledge Knowledge Environment Disseminate Disseminate Knowledge Knowledge
  20. 20. This Paper has been submitted under the guidance of K. Megala B.E – Lecturer (Computer Engg). M.Saravanan (M.E) – Lecturer (Computer Engg). Over headed by Mr.M. Ramesh Kumar, MCA.,Mphil (Computer Engg).
  21. 21. “Things that think… don’t make sense unless they link.” Thank You
  22. 22. BIBLIOGRAPHY John C. Ross. Image Processing Hand book, CRC Press. 1994. [2] Peter Mc Curry, Fearghal Morgan, Liam Kilmartin. Xilinx FPGA implementation of a pixel processor for object detection applications. In the Proc. Irish Signals and Systems Conference, Volume 3, Page(s):346 – 349, Oct. 2001. [3] M. Moore. A DSP-based real time image processing system. In the Proceedings of the 6th International conference on signal processing applications and technology, Boston MA, August 1995.Simplicity is the key to Victory.Bruce Lee

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