Personal Communication Technologies for Smart Spaces Density-Based Clustering for Content and Color Adaptive Tone Mapping

Abstract

Tone mapping operators are designed to display high dynamic range (HDR) images on low dynamic range devices. Clustering-based content and color adaptive tone mapping algorithm aims to maintain the color information and local texture. However, fine details can still be lost in low dynamic range images. This paper presents an effective way of clustering-based content and color adaptive tone mapping algorithm by using fast search and find of density peak clustering. The suggested clustering method reduces the loss of local structure and allows better adaption of color in images. The experiments are carried out to evaluate the effectiveness and performance of proposed technique with state-of-the-art clustering techniques. The objective and subjective evaluation results reveal that fast search and find of density peak preserves more textural information. Therefore, it is most suitable to be used for clustering-based content and color adaptive tone mapping algorithm.