The uneven illumination of infrared images of vehicle traffic at night leads to the weak detail texture of vehicle images,which is difficult to be identified. Therefore,an infrared polarization image enhancement method based on dual domain decomposition is proposed. The improved Retinex low illumination image illumination compensation algorithm is used to decompose the image into low frequency image and high frequency image. The low frequency image is defogged,and its contrast is optimized. Meanwhile,the high frequency image is denoised and enhanced. Thus,the low frequency and high frequency images are synthesized to realize the infrared polarization image enhancement of vehicle traffic at night. The experimental results show that this method optimizes the brightness and contrast of the enhanced image,providing more detailed information compared to the traditional method,and has an ideal visual effect.
WEI Liang, WANG Yan, HU Wen-hao, WU Zhuo-hong, YANG Hao-jun. Research on infrared image of vehicle at night based on dual domain decomposition[J]. LASER & INFRARED,2021,51(11):1538~1544