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What is Dehazing Model

Examining Fractal Image Processing and Analysis
Images obtained under adverse weather conditions, such as haze or fog, typically exhibit low contrast and faded colors, which may severely limit the visibility within the scene. Restoring the image structure under the haze layer and recovering vivid colors out of a single image is known as dehazing process. Various models such as DCP and CAP are used as prior based dehazed model.
Published in Chapter:
Image Enhancement: Application of Dehazing and Color Correction for Enhancement of Nighttime Low Illumination Image
Rasmita Lenka (KIIT University (Deemed), India), Asimananda Khandual (College of Engineering and Technology, India), Koustav Dutta (KIIT University (Deemed), India), and Soumya Ranjan Nayak (Chitkara University, India)
Copyright: © 2020 |Pages: 13
DOI: 10.4018/978-1-7998-0066-8.ch011
Abstract
This chapter describes a novel method to enhance degraded nighttime images by dehazing and color correction method. In the first part of this chapter, the authors focus on filtering process for low illumination images. Secondly, they propose an efficient dehazing model for removing haziness Thirdly, a color correction method proposed for color consistency approach. Removing nighttime haze technique is an important and necessary procedure to avoid ill-condition visibility of human eyes. Scattering and color distortion are two major problems of distortion in case of hazy image. To increase the visibility of the scene, the authors compute the preprocessing using WLS filter. Then the airlight component for the non-uniform illumination presents in nighttime scenes is improved by using a modified well-known dark-channel prior algorithm for removing nighttime haze, and then it uses α-automatic color equalization as post-processing for color correction over the entire image for getting a better enhanced output image free from haze with improved color constancy.
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