Adversary imaging condition such as in a hazy weather is a challenge in the community of image processing. To address the challenge of haze removal, several model-based approaches have been reported recently. Among them, a single image haze removal scheme based on dark channel prior (DCP) was presented in [1] and has been getting popular because of its satisfactory performance for most of cases...

Haze removal is an extremely challenging task, and object detection in the hazy environment has recently gained much attention due to popularity of autonomous driving traffic surveillance. In this work, authors propose a multiple linear regression haze model based on widely adopted dehazing algorithm named Dark Channel Prior. Training with synthetic dataset, proposed can reduce unanticipated de...

Abstract Environmental changes and human activities can cause serious degradation of murals, where sootiness is one the most common problems ancient Chinese indoor murals. In order to improve visual quality a restoration method proposed for murals based on dark channel prior Retinex by bilateral filter using hyperspectral imaging technology. First, radiometric correction denoising through band ...

The dark channel prior (DCP) algorithm has been widely used in the field of image defogging because its simple theory and clear restoration result. However, DCP significant limitations. This study clarifies relationship between halo artfacts size patch analyses reason why colour close-range white objects appears distorted restored images. An amended method is then proposed to solve these proble...

Abstract. Aiming to solve the problem of loss important image information, such as blurred details and low contrast, caused by fog, haze other meteorological influences in slope monitoring process UAV remote sensing images, a new method improving dark channel dehazing based on channel-weighted analysis compensation function is proposed training multilayer perceptron (MLP) this study. First, pri...