Image denoising with window shrink wavelet coefficients by adaptive threshold

Yifan Zhao; Jiuxian Li; Liangzheng Xia

doi:10.1117/12.737633

15 November 2007 Image denoising with window shrink wavelet coefficients by adaptive threshold

Yifan Zhao, Jiuxian Li, Liangzheng Xia

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678613 (2007) https://doi.org/10.1117/12.737633
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

We introduce an adaptive wavelet coefficients shrinkage method and apply it to image denoising. Donoho's denoising scheme which is based on thresholding the wavelet coefficients, eliminates too many wavelet coefficient without considering the image's local characteristics. In this paper we propose a new shrinkage method which can modify the magnitude of shrinkage by considering neighboring wavelet coefficients and variance of noise. So we can use more wavelet decomposition levels than other wavelet shrinkage methods to recover the noisy images. The proposed method outperforms the other methods given in literature, while its implementation and concept are both simple.

Citation Download Citation

Yifan Zhao, Jiuxian Li, and Liangzheng Xia "Image denoising with window shrink wavelet coefficients by adaptive threshold", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678613 (15 November 2007); https://doi.org/10.1117/12.737633

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