Single image dehazing via color balancing and quad-decomposition atmospheric light estimation

In recent years, single image dehazing methods have achieved good performance. But there still exists some problems, such as color distortion, excessive smoothing of image texture details and image over-saturation. For solving these problems, this paper proposes an improved single image dehazing algorithm based on Color Balancing and Quad-Decomposition (CBQD). In the pre-processing stage, we define an indicator for detecting image unbalance color channel, and correct color of images that are prone to color distortion in some special environments (e.g., sandstorms). In the dehazing phase of the algorithm, we apply the improved quad-decomposition technique for eliminating the interference of non-atmospheric light source and certain bright objects, thus can estimate atmospheric light accurately. Meanwhile, we obtain the image depth information by the linear model and estimate the initial image transmission map by fused depth map, and then refine the transmission map using a gradient domain-guided filter with edge-preserving characteristics. Finally, we can restore the scene radiance, and the dehazed images have clear edges, rich texture, no halo artifacts, and natural color. Extensive experiments verifies the superiority of CBQD over state-of-the-art image dehazing techniques in terms of both the recovery quality and efficiency.