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计算机工程 ›› 2011, Vol. 37 ›› Issue (23): 192-194. doi: 10.3969/j.issn.1000-3428.2011.23.065

• 图形图像处理 • 上一篇    下一篇

基于权值的自适应正则化超分辨率算法

刘 刚1,2,翟春伟3,戴 明1   

  1. (1. 中国科学院长春光学精密机械与物理研究所,长春 2. 中国科学院研究生院,北京 100039;3. 北华大学数学学院,吉林 吉林 130000)
  • 收稿日期:2011-05-13 出版日期:2011-12-05 发布日期:2011-12-05
  • 作者简介:刘 刚(1982-),男,博士研究生,主研方向:图像处理;翟春伟,硕士研究生;戴 明,研究员
  • 基金资助:
    国家部委基金资助项目

Super-resolution Algorithm with Adaptive Regularization Based on Weight

LIU Gang 1,2, ZHAI Chun-wei 3, DAI Ming 1   

  1. (1. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China; 2. Graduate University of Chinese Academy of Sciences, Beijing 100039, China; 3. College of Mathematics, Beihua University, Jilin 130000, China)
  • Received:2011-05-13 Online:2011-12-05 Published:2011-12-05

摘要: 不精确的配准参数会使图像重建结果不理想。为此,提出一种基于权值的自适应正则化超分辨率算法。自适应局部区域权值根据该区域的可靠性进行自适应运算,利用分水岭分割将参考图像分成不同区域,由此提升重建质量。对真实视频序列的实验结果证明该算法有效。

关键词: 超分辨率算法, 图像配准, 局部加权, 自适应正则化, 融合

Abstract: This paper proposes a Super-resolution(SR) algorithm with adaptive regularization based on weight. In case of existence of local motion and/or occlusion, regions that have local motion and/or occlusion have different noise level. To cope with this problem, it proposes to adaptively weight each region according to its reliability and the regularization parameter is simultaneously estimated for each region. The regions are generated by segmenting the reference frame using watershed segmentation. Experimental results show the effectiveness of the algorithm.

Key words: Super-resolution(SR) algorithm, image registration, local weighting, adaptive regularization, fusion

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