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Color-compressive bilateral filter and nonlocal means for high-dimensional images
Journal of Electronic Imaging ( IF 1.1 ) Pub Date : 2021-03-01 , DOI: 10.1117/1.jei.30.2.023001
Christina Karam 1 , Kenjiro Sugimoto 2 , Keigo Hirakawa 3
Affiliation  

We propose accelerated implementations of bilateral filter (BF) and nonlocal means (NLM) called color-compressive bilateral filter (CCBF) and color-compressive nonlocal means (CCNLM). CCBF and CCNLM are random filters, whose Monte-Carlo averaged output images are identical to the output images of conventional BF and NLM, respectively. However, CCBF and CCNLM are considerably faster because the spatial processing of multiple color channels are combined into a single random filtering process. This implies that the complexity of CCBF and CCNLM is less sensitive to color dimension (e.g., hyperspectral images) relatively to other BF and NLM methods. We experimentally verified that the execution time of CCBF and CCNLM are faster than the existing “fast” implementations of BF and NLM, respectively.

中文翻译:

彩色压缩双边滤波器和非局部手段,用于处理高维图像

我们提出了双边过滤器(BF)和非局部均值(NLM)的加速实现,称为彩色压缩双向过滤器(CCBF)和彩色压缩非局部均值(CCNLM)。CCBF和CCNLM是随机滤波器,其蒙特卡洛平均输出图像分别与常规BF和NLM的输出图像相同。但是,CCBF和CCNLM的速度要快得多,这是因为多个颜色通道的空间处理被组合到单个随机滤波过程中。这意味着相对于其他BF和NLM方法,CCBF和CCNLM的复杂性对颜色尺寸(例如,高光谱图像)较不敏感。我们通过实验验证了CCBF和CCNLM的执行时间分别比BF和NLM的现有“快速”实现更快。
更新日期:2021-03-04
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