Non-linear Low-Light Image Enhancement Based on Fusion Color Model Space

Abstract:

Lowlight images have problems such as low overall brightness of the image, uneven brightness, high color saturation, and image blur. To address these problems, a lowlight image enhancement algorithm fusing color model space is proposed, in which the images are processed by transforming image brightness enhancement and image color restoration to different color model spaces respectively. In the RGB color model space, the high gray levels of the image are first preprocessed and then filtered, and finally the image brightness is restored with the threecomponent enhancement function; In the HSV color model space, the image brightness is restored with the nonlinear color saturation correction function and the brightness enhancement function, and finally the processing results in the RGB and HSV color model spaces are weighted and fused. The final comparative experimental results show that the proposed method has a good effect in avoiding excessive image enhancement, color restoration and image light enhancement, and the processed images conform to the human visual characteristics.