Single I mage Haze Removal Based on Concentration Scale Prior

Dongyang Li, Guiying Tang, Li Zhao, Xiaoqin Zhang, X. Ye
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引用次数: 1

Abstract

Haze is a major degradation factor in outdoor images. Removing haze from a single image is an ill-posed problem and the performance of existing prior-based image dehazing methods is limited by the effectiveness of hand-designed features. In this paper, new dehazing method is introduced which is refined using gamma transformation and does not utilize the traditional atmospheric scattering model. The proposed method restores haze-free images without reference to corresponding clear image or estimating a depth-dependent transmission map. A novel, simple and powerful Concentration Scale Prior (CSP) is then utilized for haze removal in a single haze image to enhance gamma transformation, and its performance is verified. Experimental results show that the proposed approach achieves superior dehazing performance compared to current state-of-the-art methods.
基于浓度尺度先验的单幅图像雾霾去除
雾霾是室外图像的主要退化因素。从单个图像中去除雾霾是一个不适定问题,现有的基于先验的图像去雾方法的性能受到手工设计特征的有效性的限制。本文介绍了一种新的除雾方法,该方法不利用传统的大气散射模型,而是利用伽玛变换进行改进。该方法不需要参考相应的清晰图像或估计与深度相关的传输图,即可恢复无雾图像。利用一种新颖、简单、功能强大的浓度尺度先验算法(CSP)对单幅雾霾图像进行去雾,增强伽玛变换,并对其性能进行了验证。实验结果表明,与现有方法相比,该方法具有更好的除雾性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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