北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2012, Vol. 35 ›› Issue (6): 6-10.doi: 10.13190/jbupt.201206.6.liuhy

• 论文 • 上一篇    下一篇

全变差框架下快速恢复彩色图像的方法研究与应用

刘海英, Wu-Sheng Lu, 张承进, 孟庆虎   

  1. 1. 山东大学 控制科学与工程学院, 济南 250061;2. 加拿大维多利亚大学 电气与计算机工程系, 英属哥伦比亚省 V8W 3P6 3. 香港中文大学 电子工程学系, 香港
  • 收稿日期:2011-11-18 修回日期:2012-09-03 出版日期:2012-12-28 发布日期:2013-01-07
  • 通讯作者: 刘海英 E-mail:liuhaiying918@yahoo.com.cn
  • 作者简介:刘海英(1976-),女,博士生,Email:liuhaiying918@yahoo.com.cn 孟庆虎(1962-),男,教授
  • 基金资助:

    国家自然科学基金项目(61174044)

Research and Application for Fast Restoration of Color Images Algorithm Based on Total Variation Framework

LIU Hai-ying, Wu-Sheng Lu, ZHANG Cheng-jin, MENG Qing-hu   

  1. 1. School of Control Science and Engineering, Shandong University, Jinan 250061, China;2. Department of Electrical and Computer Engineering, University of Victoria, Victoria V8W 3P6, Canada3. Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  • Received:2011-11-18 Revised:2012-09-03 Online:2012-12-28 Published:2013-01-07
  • Contact: haiying liu E-mail:liuhaiying918@yahoo.com.cn
  • Supported by:

    RGC Competitive Earmarked Research Grant

摘要:

数字图像在采集和传输过程中很容易被噪声污染或出现不同程度的模糊现象,这给图像的后期处理和应用带来相当大的困难. 改进的算法基于交替最小化算法和新的二分法技术,在全变差能量最小化的框架下,提出一个具有自动选择最优均衡参数能力对彩色图像去除噪声及通道内和通道间模糊的算法. 实验结果表明,由于所采用的二分法的快速收敛性,改进的算法可以很快确定最优均衡参数数值,从而提高了算法的去噪声和去模糊能力及自适应能力.

关键词: 去噪, 去模糊, 全变差, 彩色图像

Abstract:

Digital images can readily be blurred in various degrees and contaminated by noise during the process of the acquisition and transmission. This inevitably leads to considerable difficulties for the subsequent processing and application of these degraded images. An algorithm that combines an alternating minimization method with a new bisection technique for denoising and within-channel/cross-channel deblurring of the color images is proposed in a total variation energy minimization framework. Experiment demonstrates that, due to the fast convergence of the bisection technique employed, the proposed algorithm is able to quickly determine optimal value of the regularization parameter, thus improving the algorithm’s denoising and deblurring performance as well as adaptation ability.

Key words: denoising, deblurring, total variation, color image

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