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

机译:基于图像重建和压缩感知的图像去噪算法

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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.
机译:本文基于图像重构和压缩感知的图像去噪算法进行研究。压缩传感理论是通过该领域专家的广泛关注,电流压缩感知理论已应用于许多领域,例如:基本压缩传感雷达,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区域。结合K-SVD算法和结构相似度测量,本文提出了基于结构相似性的图像去噪算法的稀疏表示,以改善字典。通过最终实验部件验证了性能和有效性。

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