Image Tiling For Clustering To Improve Stability Of Constant-Time Color Bilateral Filtering
Image Tiling For Clustering To Improve Stability Of Constant-Time Color Bilateral Filtering
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DOI：
10.1109/icip40778.2020.9191059
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发表时间：
2020-10
期刊：
影响因子：
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通讯作者：
Takahisa Miyamura;Norishige Fukushima;M. Waqas;Kenjiro Sugimoto;S. Kamata
中科院分区：
文献类型：
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作者：
Takahisa Miyamura;Norishige Fukushima;M. Waqas;Kenjiro Sugimoto;S. Kamata
双边滤波是一种典型的边缘保持平滑方法，在很多领域都有应用。双边滤波的主要问题是处理时间。为了解决这个问题，提出了恒定时间双边滤波。常时双边滤波是灰度图像去噪的有效方法，但对于彩色图像，常时双边滤波由于维数灾难的影响，代价很高。一些算法专门用于彩色图像的恒定时间彩色双边滤波，通过使用聚类。然而，聚类具有随机性，并且计算成本本身也很高。在本文中，我们提出了一种加速聚类的方法，使用K-means ++，平铺，和子采样，也实现了稳定性的改善。
Bilateral filtering is a typical edge-preserving smoothing and it is used in various applications. The main issue of bilateral filtering is the processing time. In order to solve this problem, constant-time bilateral filtering has been proposed. The constant-time bilateral filter is an effective method for grayscale images, but it takes high cost for color images because of the curse of dimensionality. Some algorithms specialize in constant-time color bilateral filtering for color images by using clustering. However, the clustering has randomness, and computational cost itself is also high. In this paper, we propose an acceleration method of clustering by using K-means ++, tiling, and subsampling, and also achieve improvement of the stability.