一种融合图像增强和端到端网络的海雾去除算法

Zhongli Ma, Lili Wu, Linshuai Zhang, Jiadi Li, Yuehan Zeng
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引用次数: 0

摘要

一般来说,对于有海雾的图像,雾密度分布不均匀,整个场景趋于黑暗,如果只使用图像增强算法去雾,可能会造成整体图像的色彩失真,目标图像的细节模糊;端到端去雾算法对陆地上均匀雾图像的去雾效果明显,但对雾浓、场景暗的海雾图像去雾效果不佳。本文提出了一种将图像增强与端到端网络相融合的单幅海雾图像去雾方法。首先,采用基于多尺度Retinex的图像增强技术,提高不均匀雾图像的对比度和亮度;然后,利用端到端网络提取透光率,再通过引导滤波器对透光率进行优化;最后,通过基于大气散射模型的去雾,改善了目标的边缘模糊和颜色失真。将本文方法与几种主流去雾算法进行了实验分析,分别从主观和客观两个方面对去雾质量进行了评价,实验结果表明,本文方法具有明显的去雾效果和良好的图像恢复能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Kind of Sea-fog Removal Algorithm Fusing Image Enhancement and End-to-end Network
Generally, for images with sea fog, the distribution of fog density is uneven, and the whole scenes tend to the darkness, if only the image enhancement algorithm is used to defog, it could cause color distortion of the overall image, and the details blurring of the target image; the end-to-end defogging algorithm has obvious defogging effects for the uniform mist image on the land, but it is not good for sea fog images with dense fog and dark scenes. In this paper, a kind of single sea fog image defogging method is proposed, which fuses the image enhancement with end-to-end network. Firstly, the image enhancement based on Multi Scale Retinex was adopted, to improve the contrast and brightness of the uneven fog image; Then, the end-to-end network was used to extract the transmittance, and then the transmittance was optimized by the guided filter; Finally, through removing fog based on the atmospheric scattering model, the edge blur and color distortion of the object are improved. We had experimental analysis compared our proposed method with several mainstream defogging algorithms, to evaluate the defogging quality from both subjective and objective aspects separately, the experimental results show that the proposed single-image sea fog removal algorithm has obvious defogging effects and good image restoration ability.
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