Research On CLAHE Enhancement Algorithm For Low Illumination Color Images

A clear color image can convey the most intuitive information to people.However,in the process of image acquisition,the quality of the acquired images deteriorates,and the brightness and contrast are insufficient due to the influence of weather,acquisition equipment and environment,which makes it difficult to identify detailed information.Therefore,it is of great significance to research the low illumination color image enhancement algorithm.Taking into account the limitations of traditional single algorithms,a low illumination color image enhancement algorithm combining Gamma transform and CLAHE is proposed in this paper.Firstly,the original image was converted from RGB space to HSV space,and the V component was extracted.After Gamma transformation,the V component was enhanced by CLAHE algorithm.After that,combine with the H and S components that remain unchanged and transform back to the RGB space to obtain the final enhanced image.Simulation results show that the algorithm can improve the overall brightness and contrast of the image and enrich the details of the image,but it still needs further research in terms of maintaining the clarity and suppressing the noise.In order to extract detailed information from low-illumination images,this paper proposes a low-illumination color image enhancement algorithm based on wavelet transform and CLAHE algorithm.The image is also processed in HSV space.First,the V component is wavelet decomposed to extract the low-frequency and high-frequency parts.The low-frequency part is enhanced by CLAHE algorithm,and the high-frequency part is enhanced by nonlinear transformation.A parameter is defined to stretch the Saturation S component and then merge the processed V component,S component and the unprocessed H component to obtain a new HSV image and transform it back to RGB space.The back-sharpening mask algorithm is used to mine more details.The simulation was carried out on Matlab R2015 b,and the experimental results prove that the algorithm can highlight the image details while presenting good visual effects.The shortcoming was that the algorithm took the extraction of image details as the research focus and ignored the problem of noise amplification.