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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| Main Author: | |
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| Format: | Article |
| Language: | Vietnamese |
| Published: |
H. : ĐHQGHN
2014
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| Subjects: | |
| Online Access: | http://repository.vnu.edu.vn/handle/11126/13007 |
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| Institution: | Vietnam National University, Hanoi |
| Language: | Vietnamese |
| Summary: | 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. |
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