Aiming at the problem of image quality degradation caused by insufficient illumination, a retractive algorithm of bright channel was proposed to compensate the illumination intensity of the image. The algorithm assumed that the local constant light could initially satisfy the uniformity of illumination and was similar to the scene, and the bright channel operation was used to estimate the weight of the light component. The problem of blocking was usually solved by the local processing, but this would make the compensation image texture blurred or even lost, and the fusion strategy based on image structure similarity was designed. Finally, the Retinex theoretical model was used to compensate for the light. The experimental results show that the proposed algorithm is simple and efficient, and can compensate for the low illumination area of image shadows or nighttime images. Compared with the traditional algorithm, the peak signal to noise ratio (PNSR) is improved by about 5 dB and the structure similarity (SSIM) increased by more than 7%. The algorithm in the pure software system PC (CPU frequency 2.4 G) processing 640×360 color video can reach 6-12 ms/frame, processing 320×256 infrared video to reach 4-10 ms/frame, to meet the needs of the project.