Efficient analysis of DWT thresholding algorithm for medical image de-noising
This study proposes an efficient analysis based on objective and subjective test for filtering methods of the adaptive non-linear thresholding domain in discrete wavelet transform (DWT). The ultrasound images have been captured from three region-of-interests (ROIs), which are stomach, neck, and ches...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/6129/ http://eprints.uthm.edu.my/6129/1/Efficient_Analysis_of_DWT_Thresholding.pdf |
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| Summary: | This study proposes an efficient analysis based on
objective and subjective test for filtering methods of the adaptive
non-linear thresholding domain in discrete wavelet transform
(DWT). The ultrasound images have been captured from three
region-of-interests (ROIs), which are stomach, neck, and chest.
These images have been converted into grayscale and three types
of noises have been added, including Speckle, Gaussians, and
Salt&Pepper. The objective test using Scilab 5 exhibits the
performance of thresholding design on de-noising process in
terms of signal-to-noise ratio (SNR). The visual effect has been
measured using an inspection of image experts for de-noised
image then yields the data of subjective test in terms of
mean-opinion-score (MOS). In brief, this project succeeds to
explore a new thresholding method with better performance in
both SNR and visual effect named as hybrid estimated threshold
(HET). It reveals that HET is the best filtering method to remove
the Speckle, Gaussians, and Salt&Pepper noise. |
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