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计算机工程 ›› 2012, Vol. 38 ›› Issue (21): 206-209,213. doi: 10.3969/j.issn.1000-3428.2012.21.055

• 图形图像处理 • 上一篇    下一篇

基于组合字典的图像复原约束优化算法

肖 宿1,韩国强2,肖建于1   

  1. (1. 淮北师范大学计算机科学与技术学院,安徽 淮北 235000;2. 华南理工大学计算机科学与工程学院,广州 510006)
  • 收稿日期:2012-01-30 出版日期:2012-11-05 发布日期:2012-11-02
  • 作者简介:肖 宿(1982-),男,讲师、博士,主研方向:图像处理;韩国强,教授、博士、博士生导师;肖建于,副教授、博士
  • 基金资助:
    国家自然科学基金资助项目(61070090);国家自然科学基金青年科学基金资助项目(61102117)

Constrained Optimization Algorithm for Image Restoration Based on Combined Dictionaries

XIAO Su 1, HAN Guo-qiang 2, XIAO Jian-yu 1   

  1. (1. School of Computer Science and Technology, Huaibei Normal University, Huaibei 235000, China; 2. School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China)
  • Received:2012-01-30 Online:2012-11-05 Published:2012-11-02

摘要: 提出一种基于组合字典和约束优化的图像复原算法。建立表示图像复原问题的约束优化模型,其目标函数由l2保真项和双l1正则项的线性组合构成。利用交替优化技术将模型分解为多个子问题求解,并通过邻近算子解决降噪子问题。实验结果表明,与Oliverira算法和Beck算法相比,该算法的复原速度较快,所得图像质量较好,且复原图像与原始图像的均方误差较小。

关键词: 图像复原, 约束优化模型, 稀疏表示, 交替最小化方法, 邻近算子, 软阈值函数

Abstract: According to the existing problems of image restoration in the speed and the quality, this paper presents an image restoration algorithm based on combined dictionaries and constrained optimization. A new constrained optimization model representing the image restoration problem is created. The objective function of it is composed of the l2 data fidelity term and dual l1 regularized term. Then the alternating minimization technology is used to decompose the constrained optimization model into several subproblems to be solved, and the proximal operators are introduced to solve denoising subproblems. Experimental results demonstrate the effectiveness of the presented image restoration algorithm, and compared with some similar state-of-the-art algorithms, it shows better restored results and faster speed.

Key words: image restoration, constrained optimization model, sparse representation, alternating minimization method, proximal operator, soft-thresholding function

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