基于视网膜理论的图像去雾算法综述

Haokang Wen, F. Dai, Dejin Wang
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引用次数: 5

摘要

随着计算机视觉系统的发展,图像增强已成为计算机视觉的一个重要研究方向。图像去雾技术广泛应用于卫星遥感、航空摄影、目标识别和户外监测等系统中。人们利用图像去雾技术对受雾霾影响的低质量图像进行增强或修复,以改善视觉效果,方便后期的图像处理。本文介绍了图像增强技术的应用领域,并介绍了图像去雾技术中的经典去雾算法:Retinex算法。本文利用该算法对不同场景下受雾霾影响的图片进行除雾,并根据增强效果讨论了Retinex除雾算法的优缺点。最后,分析了在不同场景下使用Retinex算法进行图像增强的有效性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey of Image Dehazing Algorithm Based on Retinex Theory
With the development of computer vision systems, image enhancement has become an important research direction in computer vision. Image defogging technology is widely used in the systems of satellite remote sensing, aerial photography, target recognition and outdoor monitoring. People use image defogging technology to enhance or repair those low-quality pictures affected by fog and haze to improve visual effects and facilitate later image processing. This paper introduces the application field of image enhancement technology, and introduces the classic defogging algorithm in image defogging technology: the Retinex algorithm. In this paper, the algorithm is used to defog the pictures affected by smog in different scenes, and the advantages and disadvantages of the Retinex defogging algorithm are discussed according to the enhanced effect. Finally, this paper analyzes the effectiveness and practicality of using the Retinex algorithm for image enhancement in different scenes.
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