Multiresolution Image Denoising via Bayesian Estimator

HU Zhan-hu

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Multiresolution Image Denoising via Bayesian Estimator

更新时间：2025-07-16

- Multiresolution Image Denoising via Bayesian Estimator
- Acta Electronica Sinica Vol. 30, Issue 1, Pages: 66-68(2002)
- 作者机构：
  
  1. 南京大学数学系,江苏,南京,210093
  2. 南京大学数学系江苏南京,210093
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN919.8
- Published：2002
- 稿件说明：
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HU Zhan-hu. Multiresolution Image Denoising via Bayesian Estimator[J]. Acta Electronica Sinica, 2002, 30(1): 66-68.
DOI：

HU Zhan-hu. Multiresolution Image Denoising via Bayesian Estimator[J]. Acta Electronica Sinica, 2002, 30(1): 66-68. DOI：

摘要

图像的小波系数具有很强的非高斯统计特性

可以建立推广的拉普拉斯先验分布

用贝叶斯估计对图像小波系数滤波来达到降噪目的.由于正交小波的正交性质能够保证白噪声干扰图像的小波系数所包含的噪声是白色的

基于正交小波变换的贝叶斯估计有较好的降噪性能.

Abstract

The wavelet subband coefficients of images have highly non-Gaussian statistics that may be modeled with generalized Laplacian distributions

and Bayesian estimation is used to suppress noise.Because the wavelet transform is orthonormal

noises in wavelet coefficients of images corrupted by additive white Gaussian noises are also Gaussian and white

and performance of denoising via Bayesian estimator based on orthogonal wavelet transform is excellent.

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