Adaptive tone-mapping operator for HDR images based on image statistics

In this paper, we present a novel segmentation method for displaying high dynamic range image based on K-means clustering. The new segmentation method uses statistical features of an image in a logarithmic luminance domain. Each divided region is applied to different global tone mapping operators respectively. The global tone mapping operator is a logarithmic tone mapping with a different user parameters. The parameters for applying to each region are calculated using a centroid which is obtained from K-means clustering. According to results of many HDR image experiments, we demonstrate that our method is faster than other local tone mapping operators and improves an image rendering performance in terms of dark area details and contrast enhancement.