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Image Processing//////////

The digital image can be optimized for the application by enhancing or altering the appearance of structures within it (based on: body part, diagnostic task, viewing preferences,etc)....

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Image Processing//////////

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  1. IMAGE PROCCESSING

  2. SYNOPSIS • 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. INTRODUCTION • Image processing involves processing or altering an existing image in a desired manner. • The next step is obtaining an image in a readable format. • The Internet and other sources provide countless images in standard formats.

  4. CONTD… • Image processing are of two aspects.. • improving the visual appearance of images to a human viewer • preparing images for measurement of the features and structures present.

  5. WHY DO WE NEED IMAGE PROCESSING?… • Since the digital image is “invisible” it must be prepared for viewing on one or more output device (laser printer,monitor,etc) • The digital image can be optimized for the application by enhancing or altering the appearance of structures within it (based on: body part, diagnostic task, viewing preferences,etc) • It might be possible to analyze the image in the computer and provide cues to the radiologists to help detect important/suspicious structures (e.g.: Computed Aided Diagnosis, CAD)

  6. ACQUIRING IMAGE… • Scientific instruments commonly produce images to communicate results to the operator, rather than generating an audible tone or emitting a smell. • Space missions to other planets and Comet Halley always include cameras as major components, and we judge the success of those missions by the quality of the images returned.

  7. TYPES OF IMAGE PROCESSING • Image-to-image transformations • Image-to-information transformations • Information-to-image transformations

  8. IMAGE-TO-IMAGE TRANSFORMATIONS • Enhancement (make image more useful, pleasing) • Restoration • Egg. deblurring ,grid line removal • Geometry • (scaling, sizing , Zooming, Morphing one object to another).

  9. IMAGE-TO-INFORMATION TRANSFORMATIONS • Image statistics (histograms) • Histogram is the fundamental tool for analysis and image processing • Image compression • Image analysis (image segmentation, feature extraction, pattern recognition) • computer-aided detection and diagnosis (CAD)

  10. INFORMATION-TO-IMAGE TRANSFORMATIONS • Decompression of compressed image data. • Reconstruction of image slices from CT or MRI raw data. • Computer graphics, animations and virtual reality (synthetic objects).

  11. HIGH RESOLUTION IMAGING • The process of obtaining an high resolution (HR) image or a sequence of HR images from a set of low resolution (LR) observations. • HR techniques are being applied to a variety of fields, 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. COLOR SPACES • Conversion from RGB (the brightness of the individual red, green, and blue signals at defined wavelengths) to YIQ/YUV and to the other color encoding schemes is straightforward and loses no information. • Y, the “luminance” signal, is just the brightness of a panchromatic monochrome image that would be displayed by a black-and-white television receiver

  13. COLOR DISPLAYS • 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. IMAGE SENSORS Digital processing requires images to be obtained in the form of electrical signals. These signals can be digitized into sequences of numbers which then can be processed by a computer. There are many ways to convert images into digital numbers. Here, we will focus on video technology, as it is the most common and affordable approach.

  15. MULTIPLE IMAGES • 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. HARDWARE REQUIREMENTS Ageneral-purpose computer to be useful for image processing, four key demands must be met: high-resolution image display, sufficient memory transfer bandwidth, sufficient storage space, and sufficient computing power. A 32-bit computer can address up to 4GB of memory(RAM).

  17. SOFTWARE REQUIREMENTS • Adobe Photoshop • Corel Draw • Serif Photoplus

  18. CONCLUSION In electrical engineering and computer science, image processing is any form of signal processing for which the input is an image, such as photographs or frames of video; the output of image processing can be either an image or a set of characteristics or parameters related to the image. Most image-processing techniques involve treating the image as a two-dimensional signal and applying standard signal-processing techniques to it.

  19. Thank You very much….. Create Knowledge Create Knowledge Apply Knowledge Apply Knowledge Apply Knowledge Apply Knowledge Apply Knowledge Seminar - Knowledge Sharing And Acquiring Environment Assimilate Knowledge Assimilate Knowledge Assimilate Knowledge Structure Knowledge Assimilate Knowledge Structure Knowledge Assimilate Knowledge Structure Knowledge Disseminate Knowledge Disseminate Knowledge Disseminate Knowledge Disseminate Knowledge

  20. Thank You “Things that think… don’t make sense unless they link.”

  21. 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.

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