Adaptively partitioned block-based contrast enhancement and its application to low light-level video surveillance

Abstract

This paper presents a dark region detection and enhancement method with low computational complexity for low-cost imaging devices. Conventional contrast enhancement methods generally have an oversaturation problem while brightness of the dark region increases. To solve this problem, the proposed method first divides an input image into dark object and bright background regions using adaptively partitioned blocks. Next, the contrast stretching is performed only in the dark region. The major advantage of the proposed method is the minimized block artifacts using optimally partitioned blocks using fuzzy logic and a refining step to accurately detect boundaries between two regions. Experimental results show that the proposed method can efficiently enhance the contrast of backlit images without the oversaturation problem. Because of low computational complexity, the proposed method can be applied to enhance very low light-level video sequences for video surveillance systems.