Low Illumination Image Enhancement Based On Bilateral Filtering And Improved CLAHE Algorithm

Today,with the rapid development of digital information technology,a large amount of image information has become a medium for transmitting information.However,due to uneven illumination and low light conditions such as dim light,the quality of the image is seriously degraded,which leads to a decrease in its use value.The traditional image enhancement algorithm is somewhat unsatisfactory.Therefore,in view of this situation,this paper studies the theory of low illumination image enhancement and some techniques,and at the same time improves the existing algorithms.The main work of the article is as follows:Firstly,it analyzes the background,significance and status of the subject,and analyzes the traditional classic low-light image enhancement algorithms in detail,such as single-scale Retinex algorithm,multi-scale Retinex algorithm,multi-scale Retinex algorithm with color recovery,histogram equalization algorithm,and the adaptive histogram equalization algorithm and the contrast-limited adaptive histogram equalization algorithm.The advantages and disadvantages of these algorithms are elaborated.Secondly,for the Retinex enhancement algorithm to deal with low illumination image enhancement,the contrast is not high,color distortion,low brightness,etc.,a color space fusion image enhancement algorithm is proposed,first in the RGB color space for the image R,G,B 3 color channels respectively perform automatic contrast stretching;convert the original image from RGB color space to HSV color space,use enhanced multi-scale Retinex algorithm to enhance the brightness component V,and convert the obtained image from HSV color space Return to the RGB color space;then perform weighted fusion on the two images in the RGB color space;finally,the fused image is subjected to gamma correction to achieve color recovery and compensation.The experimental results show that the algorithm improves the brightness and contrast of the image compared with other algorithms,while retaining more detailed information,which can effectively prevent the phenomenon of “pseudo halo”.Thirdly,based on the CLAHE image enhancement model,the problem of noise amplification and low definition appearing during image enhancement is solved.An improved CLAHE enhancement algorithm is proposed to adaptively set the imageenhancement of the cut point according to the content.Firstly,it is processed by Gaussian filtering.On the basis of filtering,it is decomposed into high frequency part and low frequency part by wavelet transform,and then the corresponding part is processed by bilateral filtering and improved CLAHE respectively.Finally,the enhanced image is obtained by wavelet reconstruction.The experimental results show that the algorithm effectively improves the image quality,prevents noise amplification and color distortion.Finally,by constructing a video surveillance system platform,the method proposed in this paper is verified on the video image.The experimental results show that the video image quality is greatly improved,the detailed information of the video image is clearer,the color is more realistic,the brightness is greatly improved,and a better enhancement effect is achieved.