Improved Retinex and Multi-Image Fusion Algorithm for Low Illumination Image Enhancemen

To solve the problems of poor image quality and low contrast in low-illumination image enhancement, this study proposes an improved Retinex and multi-image fusion algorithm for low -illumination image enhancement. First, the image to be processed is converted to the HSV color space, and the brightness of the V-channel component is adjusted by setting a threshold. Then, it is converted to the RGB color space, and three copies are made. Histogram equalization and median filtering are performed for the first part; the second part is processed by automatic brightness adjustment and bilateral filtering; the third part is processed by an improved Retinex algorithm, which uses Gaussian filtering and bilateral filtering as its surround function to estimate the illumination component of the image, and outputs the reflection image. The three processed images are transferred to the HSV color space, and the V component is fused. The H and S components follow the values of the second image component. Finally, the fused image is converted from the HSV to RGB color space, and the processed image is output. The experimental results show that the proposed algorithm not only enhances the low-illumination image but also suppresses the image noise. Furthermore, it exhibits good edge preservation and obvious details.