Abstract
In this paper, we propose a novel single image enhancement technique for defogging by using dark channel prior. The traditional dark channel prior methods for defogging have problems of high time complexity, edge effect, and failure of dark channel prior. To overcome the problems of high time complexity and edge effect, firstly, a four-point weighting algorithm is proposed to estimate the atmospheric light value accurately, and the dark channel prior is used to estimate the rough transmittance. Then, the gray-scale image of the input image is used to refine the transmittance. After that, an atmospheric scattering model is designed to restore the fog-free image. To solve the problem that the dark channel prior can not process the high brightness area, a combination of edge detection and maximum inter-class variance is used to segment the sky area and non-sky area. Finally, the improved defogging method is used for processing the non-sky area, and the enhancement algorithm via sequential decomposition is used for handling the sky area. Extensive experiments show that the improved algorithm can not only reduce the time complexity, but also effectively improve the edge effect. At the same time, it can also solve the problem of failure of dark channel prior.
Highlights
In the condition of fog and haze, the propagation of light will be affected by the scattering of suspended particles [1], which will attenuate features such as contrast and color of outdoor natural scenes captured by the image equipment
For scene 1, the improved algorithm we proposed is 5.45 larger in Peak Signal-to-Noise Ratio (PSNR) than the defogging algorithm [16] based on cost function, 5.72 larger than the PSNR of the defogging algorithm based on tolerance [12], and 3.58 larger than the PSNR of the defogging algorithm [15] based on the sky segmentation
For scene 2, the improved algorithm we proposed is 0.28 larger in Structural SIMilarity (SSIM) than the defogging algorithm [16] based on cost function, 0.28 larger than the SSIM of defogging algorithm [12] based on the tolerance mechanism, and 0.11 larger than the SSIM of defogging algorithm [15] based on the sky segmentation
Summary
In the condition of fog and haze, the propagation of light will be affected by the scattering of suspended particles [1], which will attenuate features such as contrast and color of outdoor natural scenes captured by the image equipment. The image quality is severely degraded, and it will affect people’s sight. An image enhancement technique for processing of foggy images is a very practical requirement. The techniques of removing fog from degraded images have a wide range of applications [2,3,4]. For this reason, many scholars have conducted long-term theoretical research and analysis on this direction, and many defogging algorithms have been proposed. From the perspective of image processing, existing mainstream defogging algorithms can be mainly divided into two categories: image enhancement technology-based methods and image restoration technology-based methods
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