Image Enhancement and Brightness Equalization Algorithms in Low Illumination Environment Based on Multiple Frame Sequences
Yinhua Su, Mian Hong Wu, Yan Yan · IEEE Access · 2023
Images captured in low illumination environments can affect people’s judgment of image information. To raise the visual effect of low illumination images and preserve the integrity of image information, this study proposes two algorithms. One is an image enhancement algorithm for low illumination, which combines the WASOBI image denoising method for deep denoising of images and adaptive gamma correction for brightness adjustment of images. The other is an image brightness equalization algorithm for uneven lighting. This algorithm divides the image according to the illumination area, and uses guided filtering and adaptive gamma correction to equalize the brightness of the image. The laboratory outcomes demonstrate that the proposed image enhancement algorithm can effectively reduce the noise level of the image and adjust the brightness of the image, and the algorithm has a certain degree of stability. The subjective evaluation score of the image processed using the brightness equalization algorithm is 4.7, indicating that the image has good visual effects. The objective evaluation results prove the capability of the equilibrium algorithm, and comparing to other algorithms, the algorithm has the shortest operation time, only 0.9452 seconds. Therefore, the enhancement algorithm and brightness equalization algorithm proposed in the article have certain application value.