A comparative analysis of PSNR value for images using wavelet based thresholding methods
Thresholding is a process of shrinking the small absolute coefficients value while retaining the large absolute coefficient value. It will produce finer reconstruct signal. Since this method is taking the condition that the amplitude of wavelet transform coefficients signals are much larger than noi...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/6243/ http://eprints.uthm.edu.my/6243/1/MUCET2014_shahidah.pdf |
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| Summary: | Thresholding is a process of shrinking the small absolute coefficients value while retaining the large absolute coefficient value. It will produce finer reconstruct signal. Since this method is taking the condition that the amplitude of wavelet transform coefficients signals are much larger than noises, so the unconsidered noise will be removed while holding the significant signal. This paper examine several thresholding methods namely VisuShrink (Hard Threshold), VisuShrink (Soft Threshold), BayesShrink, OTW SURE-LET and NeighShrink SURE. These five methods are implemented on standard test images and medical images to perceive its’ different performance based on the Peak Signal-to-Noise Ratio (PSNR) value. |
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