eee508_Enhancement_Part1

eee508_Enhancement_Part1 - Image Enhancement and Image...

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Image Enhancement and Image Restoration Image Enhancement ¾ Objective: accentuate or improve appearance of features, for subsequent analysis or display (possibly, but not necessarily degraded by some phenomenon). ¾ Examples of features: edges, boundaries, dynamic range and contrast. ¾ Examples of applications: 9 TV: enhance image for viewer (image quality intelligibility visual TV: enhance image for viewer (image quality, intelligibility, visual appearance). 9 Preprocessing for machine identification. ¾ Enhancement is not necessarily needed because of degradation but can be used possibly to remove degradation. EEE 508 1
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Image enhancement and Image Restoration Low contrast or dynamic range Blurred or faint edges Noise Modify low       Remove noise Sharpen faint or dynamic range blurred edges EEE 508 2
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Image Enhancement and Image Restoration Image Restoration ¾ Objective: Removal or reduction of known degradations in an image 9 Examples of degradations: blurred image, where blurring caused by kno n phenomenon kno n noise properties degradation and known phenomenon; known noise properties; degradation and geometric distortion and nonlinearities due to sensor or environment). ± Filter of camera ± Increase spatial resolution or sharpen Inverse process Low resolution or blurring due to camera or camera motion EEE 508 3
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Image Enhancement and Image Restoration Image Restoration Noisy channel Remove noise ± ± Inverse process Noise due to channel ¾ Distortion is due to known process. (known properties) 9 More knowledge then enhancement and this knowledge is exploited to correct degradation. ¾ Objective is to make restored image resemble the original image. EEE 508 4
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Image Enhancement Objective: Make processed image better in some sense then unprocessed image ± ideal desired image not well defined (not known ) and depends on problem context. ¾ Examples: 9 Images in space have often floating dust ± original image has dust in it which appears as a noise ± removing this ±noise² is enhancement, not restoration. 9 An original undegraded image cannot be further restored but can be enhanced. Main difficulty: ¾ Often difficult to quantify the criteria for enhancement. ¾ Objective of image enhancement is dependent on the application context (application-dependent) ± the criteria for enhancement are often subjective or too complex to be easily converted to useful objective measures ± image enhancement algorithms tend to be qualitative and ad hoc EEE 508 qualitative and ad hoc. 5
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Image Enhancement Types of distortions to correct: ¾ Blur (Blurring due to camera motion, defocusing, ±) ¾ Noise (assumed to be additive often for simplicity, although not necessarily the case). ¾ Contrast ¾ Examples: 9 Space photography 9 Underwater photography 9 Film grain noise EEE 508 6
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Image Enhancement Basic Tools to achieve objective: ¾ Contrast and dynamic range modification ¾ Noise smoothing ¾ Edge detection ¾ Image interpolation (motion estimation) ¾ Pseudocoloring EEE 508 7
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This document was uploaded on 03/11/2012.

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eee508_Enhancement_Part1 - Image Enhancement and Image...

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