Trends and Prospects of Techniques for Haze Removal From Degraded Images: A Survey

For the last two decades, image processing techniques have been used frequently in computer vision applications. The most challenging task in image processing is restoring images that are degraded due to various weather conditions. Mainly, the visibility of outdoor images is corrupted due to adverse atmospheric effects. The visibility of acquired images is reduced in these circumstances. Haze is an atmospheric phenomenon that reduces the clarity of an image. Due to the presence of particles such as dust, dirt, soot, or smoke, there is significant decay in the color and contrast of captured images. Haze present in acquired images causes issues in a variety of computer vision applications. Therefore, enhancing the contrast of a hazy image and restoring the visibility of the scene is essential. Since clear images are required in every application, image dehazing is an important step. Hence, many researchers are working on it. Different methods have been presented in the literature for image dehazing. This study describes various traditional and deep learning techniques of image dehazing from an analytical perspective. The main intention behind this work is to provide an intuitive understanding of the major techniques that have made a relevant contribution to haze removal. In this paper, we have covered different types of contributions toward dehazing based on the traditional method as well as deep learning approaches. With a considerable amount of instinctive simplifications, the reader is expected to have an improved ability to visualize the internal dynamics of these processes.

I. Introduction

Visible images captured in outdoor environments generally have low contrast and faded colors. It is due to the scattering of light that reflects the object’s surface before reaching the camera lens. This scattering is caused due to the presence of various atmospheric particles such as fog, smoke, dust, and soot in the atmosphere. Apart from scattering, the existence of any medium other than air or even changes in air density along the line-of-sight deviates the path of the reflected ray from the scene. Thus, in adverse weather conditions, the irradiance obtained by the camera directly from the scene point gets attenuated. The camera lens also captures the scattered light rays from other objects, called ‘environmental light’ or ‘airlight’ [1]. These phenomena cause decay in color and contrast, lower saturation, and introduce additional noise in the captured image. This type of degradation in visible images is known as the hazing effect. The hazing effect becomes more prominent as the distance between the scene and the camera increases.