ウェーブレット領域における劣化画像のガウス性雑音除去 [in Japanese] Removal of Gaussian Noise from Degraded Images in Wavelet Domain [in Japanese]
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The observed images are often corrupted by Gaussian noise. If the image is embedded in small-amplitude Gaussian noise, the noise can be removed by applying Wiener filter. Recently, the BayesShrink wavelet method has attracted considerable attention as a denoising technique. In this paper, we propose a method for removal of Gaussian noise of large amplitude as well as of small one, which can not be removed only by exploiting the BayesShrink wavelet method. Our approach is a combination of the BayesShrink wavelet method with the directional adaptive center weighted median filter. Applying the proposed method to an image corrupted by large-amplitude Gaussian noise, a clean image can be obtained.
- IEEJ Transactions on Electronics, Information and Systems
IEEJ Transactions on Electronics, Information and Systems 126(11), 1351-1358, 2006-11-01
The Institute of Electrical Engineers of Japan