An efficient dynamic window size selection method for 2-D histogram construction in contextual and variational contrast enhancement

Contrast enhancement is usually applied to those images captured in poor lighting conditions for improving the visual quality. Using interpixel contextual information, a 2-D histogram based contrast enhancement (CE) was proposed to improve image contrast and preserve more details as well. In order to maintain the balance between contrast enhancement and detail preservation, the window size of a 2-D histogram-based contrast enhancement should be adjustable based on the original image contrast and details. In addition, the computation intensive 2-D histogram based CE should be accelerated for real-time applications. Thus, we propose an efficient dynamic window size 2-D histogram construction algorithm in this paper. The proposed algorithm divides the input image into sub-blocks and assigns them appropriate window sizes, which depend upon the standard deviation and the number of distinct intensity values of each individual sub-block. Furthermore, the integral histogram is employed to be able to compute the dynamic range 2-D histogram in constant time while fluctuant window size is adopted dynamically. Experimental results demonstrate the efficacy and efficiency of the proposed algorithm.