基于多子块协同单尺度Retinex的浓雾图像增强

Aimed at the problem that the existing algorithms are not ideal to enhance foggy images with non-uniform fog distribution, this paper proposes a foggy image enhancement algorithm based on multi-block coordinated single-scale Retinex. Different from traditional Retinex algorithms that use the global statistic to obtain dynamic truncation values, the proposed algorithm first divides the image into several sub-blocks to calculate dynamic truncation values suitable for different areas with different concentrations of fog. Then,the dynamic range of detail information is adjusted with these dynamic truncation values to obtain multiple locally optimal images. Finally, the final enhancement image is calculated by fusing multiple optimal local images. This strategy enables the enhancement of detail in each area of a foggy image. The experimental results show that the proposed algorithm can effectively remove the non-uniform fog and ensure that the brightness of defogged image is kept within a range suitable for human eyes.