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基于权值的自适应正则化超分辨率算法

Super-resolution Algorithm with Adaptive Regularization Based on Weight
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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。 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.
作者 刘刚 翟春伟 戴明
机构地区 中国科学院长春光学精密机械与物理研究所 中国科学院研究生院 北华大学数学学院
出处 《计算机工程》 CAS CSCD 北大核心 2011年第23期192-194,共3页 Computer Engineering
基金 国家部委基金资助项目
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 Super-resolution（SR） algorithm image registration local weighting adaptive regularization fusion
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献9

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二级参考文献13

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计算机工程
2011年 第23期

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