Structural Adaptation for Patch-Based Image Denoising

Xiaofeng Du, Cuihua Li, Dunxu Yang
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Abstract

Most existing patch-based denoising methods are based on fixed size patch and fixed range of neighborhood, while producing state-of-the-art denoising results, the quality of the algorithm is significantly dependent on patch size. Suppose that patch size is related to image pattern, a structural adaption method for the selection of patch size is proposed in this paper. Due to the mutual similaritybetween the training samples, the simulation results illustrate the original approach can be effectively improved by adopted this method.
基于patch的图像去噪结构自适应
现有的基于patch的去噪方法大多是基于固定大小的patch和固定邻域范围,在产生最先进的去噪结果的同时,算法的质量很大程度上依赖于patch的大小。假设斑块大小与图像图案相关,提出了一种选择斑块大小的结构自适应方法。由于训练样本之间的相互相似性,仿真结果表明,采用该方法可以有效地改进原方法。
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