Abstract
Images acquired from the outdoors are often degraded owing to bad weather conditions, such as haze, fog, and rain. Various algorithms for dehazing daytime images have been introduced to eliminate the effects of haze. However, unlike daytime conditions, where sunlight is the main source of light, there are multiple regional light sources in nighttime conditions. Thus, it is difficult to effectively eliminate the effects of haze at night using dehazing algorithms that primarily target daytime hazy images. In addition, most nighttime dehazing algorithms adopt the dark channel prior (DCP) to estimate the transmission, but this approach has problems due to the spatially variant illuminations. In this paper, we propose a nighttime single image dehazing algorithm based on the structural patch decomposition. First, atmospheric light is estimated by separating the intensity and color of light. To estimate the transmission, the candidates for the transmission values are set, and the final transmission value is obtained based on a weighted summation of these candidates for each image pixel. The weights of the candidates are determined according to the structural patch information of the scene radiances estimated with these candidates. Using this approach, an appropriate transmission map can be obtained, and the dehazing procedure is shown to be robust to the mixed illumination conditions observed in the nighttime conditions. The experimental results show that the proposed algorithm effectively eliminate the effect of haze in images based on quantitative and qualitative evaluations.
Highlights
Images acquired from the outdoors are often affected by external weather conditions, such as haze, rain, and snow
EXPERIMENTAL RESULTS we compare the dehazed results obtained through the conventional methods (CMs) and the proposed method (PM) qualitatively and quantitatively
dark channel prior (DCP), a transmission estimation method, yields pleasing results in daytime conditions, but has problems in nighttime conditions owing to the presence of various light sources
Summary
Images acquired from the outdoors are often affected by external weather conditions, such as haze, rain, and snow. In the case of haze, atmospheric particles in the air absorb or scatter light, which appears as faded colors and low contrast of the images. Haze affects image acquisition via transmission which is the amount of light that reaches the camera. Hazy image is expressed as a weighted sum of scene radiance and atmospheric light according to the atmospheric scattering model [1]–[4] as follows:. Where x is the pixel location, I (x) is the hazy image, J (x) is the scene radiance, t(x) is the transmission, and A(x) is the atmospheric light. In view of the increased use of surveillance.
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