基于融合的水下图像去雾改进算法

Xinli Cao, Junqiao Xiong, Yuxin Shang, Changrui Liu, Lianying Zou
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引用次数: 0

摘要

提出了一种改进的基于融合的水下图像去雾算法。基于融合原理,我们的算法只需要通过原始退化图像获得其输入映射和权值映射。为了克服水下介质的局限性,我们定义了两个输入,分别代表原始水下图像的颜色校正和对比度增强,以及四个权重,旨在增强被介质散射和吸收退化的远处物体的可见度。我们的方法是单图像方法,不需要专门的硬件或水下条件或场景结构的知识。我们的融合框架还通过应用有效的边缘去噪策略来支持相邻图像之间的时间相关性。增强图像的特点是降低了噪点水平,改善了黑暗区域的曝光,增加了整体对比度,同时显着增强了最精细的细节和边缘。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Algorithm for Defogging Based on Fused Underwater Images
This paper describes an improved algorithm for de-fogging based on fusion underwater images. Based on the fusion principle, our algorithm only needs to obtain its input map and weight map through the original degraded image. To overcome the limitations of underwater media, we define two inputs, representing color correction and contrast enhancement of the original underwater image, and four weights, which aim to enhance distant objects degraded by medium scattering and absorption visibility. Our method is a single-image method and does not require specialized hardware or knowledge about underwater conditions or scene structure. Our fusion framework also supports temporal correlation between adjacent images by applying an efficient edge denoising strategy. The enhanced image features reduced noise levels, improved exposure in dark areas, and increased overall contrast, while significantly enhancing the finest details and edges.
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