A hybrid image enhancement method
Kai‐Lung Hua, Weilun Sun, Chiao-Wen Lu, Shih-Che Chien, Yung-Yao Chen · 2016
For enhancing image contrast, global histogram equalization uses the histogram information of the entire input image for designing its transformation function. However, such global approach is suitable for overall enhancement, and it fails to adapt with the local image brightness features. In this paper, we present an effective method for image contrast enhancement that combines local information and global information. In local enhancement, we get multiple intensity mapping functions from the recursive mean-separate histogram equalization method. According to intensity level, we map different transformation functions to the center sub-block and its neighboring sub-blocks. This method is combined with unsharp masking to enhance the local detail of the image. Experimental results show the effectiveness of the proposed method.