计算机科学 ›› 2020, Vol. 47 ›› Issue (11): 168-173.doi: 10.11896/jsjkx.190900004
曹义亲, 谢舒慧
CAO Yi-qin, XIE Shu-hui
摘要： 针对特定类别图像去噪算法存在部分区域纹理丢失以及相似块搜索较为耗时的问题,文中提出了新的基于网格搜索的特定类别图像去噪算法。使用SSIM在特定类别数据集中选取与噪声图像相似的候选数据集;为加快相似块的搜索速度,通过网格状粗尺度搜索框遍历候选图像集,使用kNN算法寻找网格中与噪声块接近的候选块;为寻找与噪声块更接近的候选块,依据候选块中心位置构造细尺度搜索框,遍历细尺度搜索框筛选候选块与噪声块之间欧氏距离最接近的相似块;结合相似块与全局稀疏结构正则化中的残差分量来恢复噪声图像的潜影。实验结果表明,网格搜索策略能加快相似块的选择速度,使用残差分量不仅能去除图像噪声,还能更好地保留图像边缘处的信息。
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