Depth-guided adaptive contrast enhancement using 2D histograms

Abstract

A novel contrast enhancement (CE) algorithm using 2-dimensional (2D) histograms, which transforms pixel values adaptively based on the depth information, is proposed in this work. In general, foreground objects convey more important visual information than background regions. Hence we assign high CE priorities to foreground pixels using the depth values and generate a depth-guided 2D histogram. Then, we stretch the gray-level differences of adjacent foreground pixels more strongly than those of adjacent background pixels. Moreover, to enhance background regions as well, we design two transformation functions for the foreground and the background separately. By combining the two functions according to pixel depths, we obtain an adaptive space-variant transformation function, which is finally used to reconstruct the output image. Experimental results show that the proposed algorithm outperforms conventional CE algorithms by enhancing salient foreground objects efficiently and preserving background details faithfully.