HDR image retrieval by using color-based descriptor and tone mapping operator

Abstract

Various methods have been performed for the purpose of Low Dynamic Range (LDR) image retrieval. However, no major work concerning the High Dynamic Range (HDR) image indexing has been widely diffused yet. We therefore propose a method that tackles the problem of efficiently and accurately retrieving HDR images. The proposed system is based on a hybrid descriptor which combines two color features. The first one is histogram based on the hue–saturation–value (HSV) color space that approaches the perception of human vision, whereas the second comprises the first- and second-order moments of the color bands. As a dissimilarity measure, we retained the Manhattan distance. In the second part of our work, we proposed an automatic tone mapping operator (TMO) to get an overview on the result images by using Standard Dynamic Range (SDR) devices. Comparisons with recent state-of-the-art TMOs have shown that our TM method produces LDR images with adequate quality while maintaining low complexity. Finally, to test our retrieval system, we have created two databases. Experimental evaluation showed that our system supports HDR images while achieving satisfying results in terms of accuracy and computational cost.