Infrared image contrast enhancement using adaptive histogram correction framework

To enhance infrared images' contrast and visual effect, this paper proposes a contrast enhancement method based on adaptive histogram correction and equalization. Unlike the previous histogram equalization method, this method combines adaptive histogram correction and histogram equalization to effectively reduce artifacts and insufficient local detail enhancement caused by traditional methods. In our method, a more uniform histogram is first obtained by recursive separation weighted histogram equalization, then a weighted averaging method is used to establish a connection between this histogram and the original histogram to correct the histogram, and finally, the corrected histogram is used to establish a mapping relationship between the input gray levels and the output gray levels. The experimental results show that the infrared image contrast enhancement using this method is better in terms of detail representation in dark areas, overall image brightness maintenance, contrast enhancement, and suppression of artifacts, and is better than or similar to existing methods.