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Image filtering algorithm based on digital TV filter coupling with residual error correction

机译:基于数字电视滤波器和残差校正的图像滤波算法

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In this paper, we propose a digital TV (total variation) restoration model based on graph theory, motivated by the classical continuous TV restoration model of Rudin,Osher and Fatemi. We investigate its advantages in de-noising and enhancing non-texture images, and also analyze its shortcomings in deal with the texture images. Following the ideas of Yves Meyer in a total variation minimization framework of L. Rudin, S.Os-her and E.Fatemi, we propose a new image filtering algorithm subsuming the digital TV filter and the residual error correction scheme. In our algorithm, we decompose a given image /sub u//sup 0/ into a sum of two parts u + v by two-step method, where in the first step digital TV filter is used to obtain u which is the sketchy approximation of /sup u//sub 0/ , while the texture information in v is extracted by the residual error correction scheme using wavelet and wavelet packet thresholding technique. Experiments show our hybrid algorithm has more abroad application perspective and has better performance than digital TV filtering algorithm on real image.
机译:在本文中,我们提出了一种基于图论的数字电视(总变化量)恢复模型,该模型受Rudin,Osher和Fatemi的经典连续电视恢复模型的启发。我们研究了其在消噪和增强非纹理图像方面的优势,并分析了其在处理纹理图像方面的缺点。在L.Rudin,S.Os-her和E.Fatemi的总变化最小化框架中,按照Yves Meyer的想法,我们提出了一种新的图像滤波算法,该算法将数字电视滤波器和残差纠错方案都包括在内。在我们的算法中,我们通过两步法将给定的图像/ sub u // sup 0 /分解为两部分u + v的和,其中在第一步中,数字电视滤波器用于获得u,这是粗略近似/ sup u // sub 0 /的值,而v中的纹理信息是使用小波和小波包阈值技术通过残差纠错方案提取的。实验表明,我们的混合算法在实际图像上比数字电视滤波算法具有更广阔的应用前景和更好的性能。

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