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Digital images captured in hazy conditions suffer from colour distortion and loss of contrast, posing difficulties in being applied for further applications. Due to the existed challenge and its great significance, a large amount of research has been conducted for image de-hazing. Among the image haze removal methods, the algorithm based on dark channel prior is proved to be the most effective. Furthermore,...
This paper proposes a single image dehazing based on deep neural network that is to deal with haze image. In this paper, we build up a deep neural network to restore the hazy image. We test our method both objective and subjective and compare with classical method for dehazing. Our test shows that our method works better than the others in reducing Halo effect and also our method does well in restore...
Currently, China has the fastest growing air transportation market in the world. Resilience to external events is critical to ensure an efficient and reliable transportation of passengers. This study investigates the robustness of the Chinese airline network under disruptions at their critical airports as well as the evolution of the networks' robustness from the year 2010 to 2015. Among the 24 Chinese...
In this paper, we address a haze removal problem from a single nighttime image, even in the presence of varicolored and non-uniform illumination. The core idea lies in a novel maximum reflectance prior. We first introduce the nighttime hazy imaging model, which includes a local ambient illumination item in both direct attenuation term and scattering term. Then, we propose a simple but effective image...
Underwater images suffer from low contrast and color distortion due to the existence of dust-like particles and light attenuation. Some previous works using the patch-based priors, e.g. adaptations of the dark channel prior, cannot achieve satisfactory results in both contrast enhancement and color restoration in the underwater environment. In this paper, we propose a novel underwater image restoration...
To overcome the degraded images taken in hazy weather, an adaptive restoration method based on improved contrast enhanced restoration was proposed. Firstly, by quadtree subdivision searching method, the sky area of multi-channel polarization image are extracted automatically, and the atmospheric light and degree of polarization are calculated; Second, scene depth information of image are calculated...
The traditional image defogging algorithm based on polarization characteristic is mostly optimized for polarization degree, atmospheric light intensity and depth information, but the traditional defogging algorithm based on polarization characteristics in heavy fog is not satisfactory. In this paper, a new color space conversion algorithm using dark channel prior for polarization image defogging was...
Traditional dehazing algorithm based on dark channel prior may suffer weak robustness against the variation of hazy weather and may fail in bright regions. To resolve these issues, this paper proposes an improved adaptive dehazing algorithm based on dark channel prior. Our method can adaptively calculate dehazing parameter, such as the degree of haze removal. Here the dehazing parameters are local,...
This paper presents a real-time visibility enhancement algorithm for effective underwater visual simultaneous localization and mapping (SLAM). Unlike an aerial environment, an underwater environment contains larger particles and is dominated by a different image degradation model. Our method starts with a thorough understanding of underwater particle physics (e.g., forward, back, multiple scattering,...
Outdoor images taken in bad weather conditions, such as haze and fog, look faded and have reduced contrast. Recently there has been great success in single image dehazing, i.e., improving the visibility and restoring the colors from a single image. A crucial step in these methods is the calculation of the air-light color, the color of an area of the image with no objects in line-of-sight. We propose...
Outdoor scene visibility deteriorates due to presence of haze or fog. Several dehazing techniques have found its application in fields of surveillance, detection, restoration and tracking. The techniques proposed till date are computationally complex and time consuming and thus not suited for real-time applications. The degraded images mostly suffer from reduced contrast. The technique proposed in...
Contrast and color of the captured images are degraded under bad weather conditions mostly in fog due to attenuation and airlight of the scene radiance coming towards the observer. To minimize road accidents through vision enhancement in turbid weather, an efficient visibility enhancement using fog removal technique plays a very significant role as fog greatly reduces the contrast and hence affects...
The limited visibility caused by fog and haze is a most important problem for several function therefore haze removal by these images for visibility improvement is necessary. In this paper, haze removal is done by make use of the dark channel prior procedure and estimation of the Atmospheric light technique. Dark channel region is calculated by using dark channel algorithm then the atmospheric variation...
Context-based modeling of 3D urban terrain has become increasingly popular in the last two decades. Typically, orthophotos are used for texturing ground. In order to increase locational awareness, it is useful to eliminate from the orthophotos those object instances which frequently appear and disappear in the terrain. Vehicles are good examples of such instances. Assuming that vehicles were detected...
Haze is a common atmospheric phenomenon in our dairy life. Image taken in foggy environment will have a loss of contrast and color due to the effect of haze. The hazed image would make a big trouble to some vision-driven applications since low accuracy in the scene recognition or object detection. Especially, single image dehazing is one of the challenging issue in the scene dehazing problem. In this...
A genetic programming (GP)-based framework to learn the effective feature representation for image dehazing is proposed in this work. In GP, an individual program is randomly generated and genetically evolved to achieve the desired goal. To make GP estimate haze in an input image, a set of operators and operands is designed, each of which is a primitive of a GP program. Specifically, we provide four...
Images taken under fog or haze have their visibility reduced due to the existence of aerosols in the atmosphere. Image dehazing methods try to recover haze-free versions of these images by removing the effect of haze. Methods proposed till now are exclusively for daytime scene images or for night-time scene. The method we propose here can dehaze an image independent of whether it was captured during...
Single image dehazing is an active research area in the image proceesing field. A popular model-based scheme based on the dark channel prior (DCP) prevails in single image dehazing because of its satisfactory performance for most of cases. However, it is well-known that the DCP scheme suffers from high computational cost to refine the transmission map. It is observed that the problem in the DCP scheme...
With the wide range of features and charms, security surveillance systems are nowadays collective in most industries around the globe. These applications can range from mugging and destruction deterrence to traffic and weather monitoring and more. The surveillance systems are major part in investigations related to crimes and all. But the core problem with the pictures taken with the surveillance...
Combinatorial test design (CTD) is an effective and widely used test design technique. CTD provides automatic test plan generation, but it requires a manual definition of the test space in the form of a combinatorial model. One challenge for successful application of CTD in practice relates to this manual model definition and maintenance process. Another challenge relates to the comprehension and...
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