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

机译:基于图像重构和压缩感知的图像降噪算法

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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:在本文中,我们基于图像重建和压缩感知对图像去噪算法进行了研究。压缩感知理论是由该领域的专家广泛关注的,目前的压缩感知理论已被应用于许多领域,例如:基本的压缩感知雷达,作为医学图像处理的无线传感器网络。因此,我们将其应用于图像降噪区域。结合K-SVD算法和结构相似性度量,提出了基于结构相似性的图像去噪算法的稀疏表示,以改进字典。通过最后的实验部分验证了性能和有效性。

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