Iterative normalized double threshold selection for Adaptive Unsharp Masking
Image processing has been the focal point of considerable research activity in the last decade mainly because of its wide application areas. With the help of an existing image enhancement technique, Adaptive Unsharp Masking (AUM), proposed optimum parameters selection procedure has significant effec...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | Image processing has been the focal point of considerable research activity in the last decade mainly because of its wide application areas. With the help of an existing image enhancement technique, Adaptive Unsharp Masking (AUM), proposed optimum parameters selection procedure has significant effect in terms of sharpness and contrast adjustment in images. The experimental results prove that AUM technique converges to a minimum mean square error especially with proper selection of lower and upper limit threshold values, which are the most dominant parameters amongst the others, in a practical way: Iterative normalized double thresholding. |
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ISSN: | 2165-0608 2693-3616 |
DOI: | 10.1109/SIU.2011.5929578 |