An Over-complete Learned Dictionary-Based Image De-noising Method

CAI Ze-min; LAI Jian-huang

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An Over-complete Learned Dictionary-Based Image De-noising Method

更新时间：2025-07-16

- An Over-complete Learned Dictionary-Based Image De-noising Method
- Acta Electronica Sinica Vol. 37, Issue 2, Pages: 347-350(2009)
- 作者机构：
  
  1. 中山大学数学与计算科学学院,广东,广州,510275
  2. 中山大学信息科学与技术学院,广东,广州,510275
  3. 广东省信息安全技术重点实验室,广东,广州,510275
  4. 中山大学数学与计算科学学院广东广州,510275
  5. 中山大学信息科学与技术学院广东广州,510275
  6. 广东省信息安全技术重点实验室广东广州,510275
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.73
- Published：2009
- 稿件说明：
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CAI Ze-min, LAI Jian-huang. An Over-complete Learned Dictionary-Based Image De-noising Method[J]. Acta Electronica Sinica, 2009, 37(2): 347-350.
DOI：

CAI Ze-min, LAI Jian-huang. An Over-complete Learned Dictionary-Based Image De-noising Method[J]. Acta Electronica Sinica, 2009, 37(2): 347-350. DOI：

摘要

基于超完备字典的图像稀疏表示因其具有稀疏性、特征保持性、可分性等特点而被广泛应用于图像处理.本文提出一种超完备字典学习算法并应用于图像去噪.将字典学习等价于一个二次规划问题

并提出适合于大规模运算的投影梯度算法.学习所得字典能有效描述图像特征.基于此超完备学习字典

获得图像的稀疏表示

并恢复原始图像.实验结果表明

与小波类去噪方法相比

本文的学习算法能更好地去除图像噪声

保留图像细节信息

获得更高的PSNR值.

Abstract

Images sparse representations over over-complete dictionaries have a wide application in image processing due to the properties of sparsity

integrity and separability.This paper proposes a dictionary learning algorithm which is applied to image de-noising.The dictionary learning problem is expressed as a box-constrained quadratic program and a fast projected gradient method is introduced to solve it.The learned dictionary describes the image content effectively.Experimental results show that:in comparison with the wavelet-based de-noising methods

our learning-based algorithm has better de-noising ability

keep more detail image information and improve the peak signal-to-noise ratio.

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