One of the major issues related to dehazing methods (single or multiple image based) evaluation is the absence of the haze-free image (ground-truth). This is also a problem when it concerns the validation of Koschmieder model or its subsequent dehazing methods. To overcome this problem, we created a database called CHIC (Color Hazy Image for Comparison), consisting of two scenes in controlled e...

Natural images captured in bad weather conditions often suffer from poor visibility. Dehazing, the process of removing haze from a single input image or multiple images, is a crucial task in image and video processing, which is quite challenging because the number of freedoms is lager than the number of observations. In this paper, we propose a novel method to reduce the block artifacts and hal...

We propose a new end-to-end single image dehazing method, called Densely Connected Pyramid Dehazing Network (DCPDN), which can jointly learn the transmission map, atmospheric light and dehazing all together. The endto-end learning is achieved by directly embedding the atmospheric scattering model into the network, thereby ensuring that the proposed method strictly follows the physicsdriven scat...

Image dehazing deals with the removal of undesired loss of visibility in outdoor images due to the presence of fog. Retinex is a color vision model mimicking the ability of the Human Visual System to robustly discount varying illuminations when observing a scene under different spectral lighting conditions. Retinex has been widely explored in the computer vision literature for image enhancement...

Single image dehazing is challenging because it is massively ill-posed. Haze removal based on dark channel prior is effective, but refining the transmission map with closed-form matting is computationally expensive. Recent work discovered that using guided filter to refine the transmission map is feasible. In this paper, we elaborate single image dehazing by combining dark channel prior and gui...

This paper presents a review on edge-preserving decomposition based image haze removal. When the background has dust particles or hazes its image quality and color is degraded. It is well-known that local filtering-based edge preserving smoothing method suffers from halo artifacts. In this paper a survey of many different methods for haze removal just like Laplacian-based visibility restoration...

In this paper, we propose a new fast dehazing method from single image based on filtering. The basic idea is to compute an accurate atmosphere veil that is not only smoother, but also respect with depth information of the underlying image. We firstly obtain an initial atmosphere scattering light through median filtering, then refine it by guided joint bilateral filtering to generate a new atmos...

Single image dehazing is a challenging under-constrained problem because of the ambiguities of unknown scene radiance and transmission. Previous methods solve this problem using various hand-designed priors or by supervised training on synthetic hazy image pairs. In practice, however, the predefined priors are easily violated and the paired image data is unavailable for supervised training. In ...

Current environmental monitoring devices are limited in their capability of measuring atmospheric particulate matter (PM) over large areas. Quantifying the visual degrading effects of atmospheric scattering in digital images of urban scenery and correlating these effects to PM levels is a vital step in more practically monitoring our environment. Currently, image haze removal (or dehazing) tech...

Underwater environments often cause color scatter and color cast during photography. Color scatter is caused by haze effects occurring when light reflected from objects is absorbed or scattered multiple times by particles in the water. This in turn lowers the visibility and contrast of the image. Color cast is caused by the varying attenuation of light in different wavelengths, rendering underw...