Robust Single-Image Dehazing

Abstract

This paper proposes a new single-image dehazing method, which is an important preprocessing step in vision applications to overcome the limitations of the conventional dark channel prior. The dark channel prior has a tendency to underestimate transmissions of bright regions or objects that can generate color distortions during the process of dehazing. In order to suppress the distortions in a large sky area or a bright white object, the sky probabilities and the white-object probabilities calculated in the non-sky area are proposed. The sky area is detected by combining the advantages of a region-based and a boundary-based sky segmentation in order to consider various sky shapes in road scenes. The performance of the proposed methods is evaluated using synthetic and real-world datasets. When compared to conventional methods in the reviewed literature, the proposed method produces significant improvements concerning visual and numerical criteria.

Single Image Dehazing Using Global Illumination Compensation

“…For each position, the product of other elements around the central element is calculated to form a single output matrix element. The calculation process is shown in Equation (6). Based on computation, the brighter areas in the input image are enhanced and displayed in Lw.…”

“…Dhara et al [5] used weighted least-squares filtering and color correction on DCP to optimize the dehazing effect. Kim [6] proposed a sky detection method using region-based and boundary-based sky segmentation, which enables DCP to perform image restoration for sky of various shapes. Chung et al [7] estimated, by analyzing a large number of optimal scattering coefficients and the distribution between dark channels, an appropriate scattering coefficient.…”