Image de-noising algorithm based on image reconstruction and compression perception

Baohui Zhao, Wenzhun Huang, H. Wang, Zhe Liu
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引用次数: 10

Abstract

In this paper, we conduct research on the image de-noising algorithm based on the image reconstruction and compression perception. Compressed sensing theory was proposed by the wide attention of experts in the field, the current compression perception theory has been applied to many fields, such as: basic compressed sensing radar, wireless sensor network as medical image processing. Therefore, we apply it on the area of the image de-noising. Combined with K-SVD algorithm and structure similarity measures, this paper puts forward the sparse representation of image de-noising algorithm based on structure similarity, to improve the dictionary. The performance and effectiveness are verified through the final experiment part.
基于图像重构和压缩感知的图像去噪算法
本文研究了基于图像重构和压缩感知的图像去噪算法。压缩感知理论的提出受到了该领域专家的广泛关注,目前压缩感知理论已经应用到许多领域,如:压缩感知雷达基础、无线传感器网络作为医学图像处理。因此,我们将其应用于图像去噪领域。结合K-SVD算法和结构相似度度量,提出了基于结构相似度的图像去噪稀疏表示算法,对字典进行了改进。通过最后的实验验证了系统的性能和有效性。
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