Low Illumination Image Enhancement Algorithm Based on HSV-RNET

Abstract

Aiming at the problems of color distortion, blurred edge and large noise in the RetinexNet image enhancement algorithm, a low-illumination image enhancement algorithm based on HSV-RNET is proposed. First, convert the image to HSV color space image, and enhance the illuminance image V separately; then, add denoising loss to control the noise of reflected image in the decomposition network, and add color loss function to the enhancement network to improve the color distortion of the image; secondly, after denoising the decomposed reflection image R, add Canny image sharpening and then combine with the enhanced illumination image I^; finally, convert the HSV image to RGB image. The experimental results show that, compared with image enhancement algorithms such as LIME and SRIE, the algorithm proposed in this paper can effectively reduce the color distortion and edge blur, and improve the visual effect of the image. There are obvious advantages in the quality evaluation index.