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.