Single Image Haze Removal Using Haze Color Prior
Ningtao Ma, Ru Yi, Mingyang Sun, Liangyu Ruan · 2024
Image dehazing is a fundamental low-level vision task aimed at recovering clear visual scenes from images affected by haze. Addressing the haze effects in real outdoor environments, we propose a simple yet effective image prior: haze color prior. Leveraging this prior knowledge, we devise a computational model for estimating the coarse-level transmission map and obtain a refined transmission map through an adaptive gamma correction method based on the dark channel prior. Subsequently, employing our proposed two-stage filtering strategy, appropriate local atmospheric light can be acquired. Finally, integrating with the atmospheric scattering model, we can restore high-quality haze-free images. Experimental results prove that compared to other existing advanced methods, this algorithm excels in dehazing, enhancing image contrast, and preserving details.