ABC-NET: Avoiding Blocking Effect & Color Shift Network for Single Image Dehazing Via Restraining Transmission Bias

In recent years, single image dehazing methods based on Atmospheric Scattering Model (ASM) have achieved state-of-the-art results. But the dehazing outputs of those methods suffer from color shift and blocking effect. Our preliminary experiments show that the negative bias of the estimated transmission and the bias of tiny transmission value will cause serious color shift. Therefore, in this study, a new loss function (TransLoss) and a new natural activation function (NAF) are proposed to restrain negative bias of transmission and avoid tiny transmission value from being activated, respectively. Moreover, it is noted that the block effect is caused by patch-level transmission estimation mechanism in existing dehazing models. To address this issue, a new pixel-level transmission estimation module (ETM) is dedicated designed to avoid blocking effect. In the end, an end-to-end CNN dehazing network avoiding color shift and blocking effect is developed, termed as ABC-Net. Experimental results indicate that the ABC-Net outperforms four comparison methods on both synthetic and real-world images.