Research On Enhancement Algorithm Of Low Illumination Color Image

With the continuous progress of society and the rapid development of science and technology,monitoring equipment has become an indispensable part of people’s daily life.In the night environment,the picture captured by the monitoring device is often very bright due to insufficient light.This not only affects the effectiveness of monitoring equipment,but also may bring potential safety hazards to people.Therefore,the enhancement study of low-light images at night is an important topic.The specific work of this article is as follows:(1)The research status of low-illumination image enhancement algorithm at home and abroad and the relevant theoretical knowledge involved are introduced,two classical theories are deeply studied,and the advantages and shortcomings of the algorithm are compared through experimental code reproduction of related algorithms and some literature algorithms,and its key technologies in the direction of low-illumination image enhancement are explained.The relevant theoretical basis and basic principles of the image enhancement algorithm mentioned in this paper are introduced,and the importance of each parameter in image enhancement is pointed out.Finally,the focus is on how the image enhancement algorithm is implemented and verified.(2)Aiming at the problems of serious noise and uneven brightness after the existing night image enhancement algorithm.This paper proposes an optimization algorithm based on the adaptive histogram equalization algorithm of limited contrast,which preprocesses the image before image enhancement,that is,converts the image color space,converts from RGB to HSV color space,and then performs minimum filtering of the luminance V channel,which aims to remove the salt and pepper noise,etc.,and use the adaptive gamma function to correct the image color.After preprocessing,the image is enhanced by the CLAHE algorithm,and finally the edge information is smoothed and optimized by guided filtering.The experimental results show that the proposed algorithm has obvious image brightness enhancement,and compared with several other low-illumination image enhancement algorithms based on histogram equalization,it has a significant effect on removing pepper and salt noise in the image,and has more advantages in improving the standard deviation and information entropy values.(3)Aiming at the defects of low color saturation and poor detail display of low-illumination images,this paper proposes an improved image enhancement algorithm based on Retinex algorithm with color recovery factor,which guides the filtering of the input image to extract high-frequency components while retaining the edge details of the image;Gamma correction of the luminance V channel is carried out according to the average brightness value of the image to ensure the improvement of the brightness of the image.At the same time,the image is processed by the multi-scale Retinex algorithm with color restoration,and then the sub-images containing different information are weighted and fused to improve the brightness of the image under the premise of ensuring the integrity of the detailed information.The algorithm is not only able to improve the brightness of the image,but also better preserve image details and color information.By experimentally comparing the improved algorithm with the classical algorithm and other paper algorithms,the algorithm not only improves the overall brightness of the image,but also inherits the naturalness and integrity of the original image,compared with several other low-illumination image enhancement algorithms of different methods,the proposed method also has more advantages in peak signal-to-noise ratio and structural similarity.