An adaptive enhancement method for low illumination color images

In order to effectively improve the visual effect and image quality of color images under low illumination conditions, we propose an image enhancement method based on HSV and CIEL*a*b* color spaces for adaptively enhancing color image under low illumination conditions. The proposed method takes into account the characteristics of low illumination color images, and has the strategies of contrast, brightness enhancement, and color saturation correction. We utilize our proposed adaptive chaotic particle swarm optimization algorithm in this paper combined with gamma correction to improve the overall brightness of the image, and generate the best brightness adjustment effect in the proposed algorithm. In addition, our improved adaptive stretching function is used to enhance the image saturation. The experimental results show that compared with other traditional and latest color image enhancement algorithms, the proposed algorithm significantly enhances the visual effect of the low illumination color images. It can not only improve the contrast of low illumination color images and avoid color distortion, but also effectively improve the brightness of the image and provide more detail enhancement while maintaining the naturalness of the image.

Automated summary

The proposed image enhancement method based on HSV and CIEL*a*b* color spaces effectively improves the visual effect of color images under low illumination conditions. It focuses on contrast, brightness enhancement, and color saturation correction, utilizing an adaptive chaotic particle swarm optimization algorithm and gamma correction to improve brightness, as well as an improved adaptive stretching function for saturation enhancement.