Analysis the Statistical Parameters of the Wavelet Coefficients for Image Denoising
Image denoising is aimed at the removal of noise which may corrupt an image during its acquisition or transmission. De-noising of the corrupted image by Gaussian noise using wavelet transform is very effective way because of its ability to capture the energy of a signal in few larger values. This...
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oai:112.137.131.14:11126-130072017-10-27T01:42:21Z Analysis the Statistical Parameters of the Wavelet Coefficients for Image Denoising Nguyễn, Vĩnh An Thống kê Tách nhiễu ảnh Hệ số wavelet Image denoising is aimed at the removal of noise which may corrupt an image during its acquisition or transmission. De-noising of the corrupted image by Gaussian noise using wavelet transform is very effective way because of its ability to capture the energy of a signal in few larger values. This paper proposes a threshold selection method for image de-noising based on the statistical parameters which depended on sub-band data. The threshold value is computed based on the number of coefficients in each scale j of wavelet decomposition and the noise variance in various sub-band. Experimental results in PSNR on several test images are compared for different de-noise techniques. 2014-12-10T03:37:32Z 2015-08-26T09:34:14Z 2014-12-10T03:37:32Z 2015-08-26T09:34:14Z 2013 Article 7 tr. http://repository.vnu.edu.vn/handle/11126/13007 vi application/pdf H. : ĐHQGHN |
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Thống kê Tách nhiễu ảnh Hệ số wavelet |
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Thống kê Tách nhiễu ảnh Hệ số wavelet Nguyễn, Vĩnh An Analysis the Statistical Parameters of the Wavelet Coefficients for Image Denoising |
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Image denoising is aimed at the removal of noise which may corrupt an image during
its acquisition or transmission. De-noising of the corrupted image by Gaussian noise using wavelet transform is very effective way because of its ability to capture the energy of a signal in few larger values. This paper proposes a threshold selection method for image de-noising based on the
statistical parameters which depended on sub-band data. The threshold value is computed based on
the number of coefficients in each scale j of wavelet decomposition and the noise variance in
various sub-band. Experimental results in PSNR on several test images are compared for different
de-noise techniques. |
format |
Article |
author |
Nguyễn, Vĩnh An |
author_facet |
Nguyễn, Vĩnh An |
author_sort |
Nguyễn, Vĩnh An |
title |
Analysis the Statistical Parameters of the Wavelet Coefficients for Image Denoising |
title_short |
Analysis the Statistical Parameters of the Wavelet Coefficients for Image Denoising |
title_full |
Analysis the Statistical Parameters of the Wavelet Coefficients for Image Denoising |
title_fullStr |
Analysis the Statistical Parameters of the Wavelet Coefficients for Image Denoising |
title_full_unstemmed |
Analysis the Statistical Parameters of the Wavelet Coefficients for Image Denoising |
title_sort |
analysis the statistical parameters of the wavelet coefficients for image denoising |
publisher |
H. : ĐHQGHN |
publishDate |
2014 |
url |
http://repository.vnu.edu.vn/handle/11126/13007 |
_version_ |
1680964025551159296 |