ALSP+: Fast Scene Recovery via Ambient Light Similarity Prior

计算机科学 计算机视觉 人工智能 相似性(几何) 计算机图形学(图像) 图像(数学)
作者
Lei He,Zunhui Yi,Jinshi Liu,Chaoyang Chen,Ming Lu,Zhipeng Chen
出处
期刊:IEEE transactions on image processing [Institute of Electrical and Electronics Engineers]
卷期号:34: 4470-4484 被引量:9
标识
DOI:10.1109/tip.2025.3586514
摘要

The absorption and scattering of light in different turbid media cause images to suffer from poor visibility and contrast, which severely affects the performance of many computer vision tasks. To address this issue, we propose a fast scene recovery method based on the Ambient light similarity prior (ALSP). In this method, the ambient light similarity metric is designed from both magnitude and orientation, which is embedded into the optical imaging model, and the estimation of scene transmission is derived by simplification and approximation. The estimation of the transmission map is very simple, and its time complexity is O(N), where N is the size of the input image. Moreover, we propose a progressive manner to determine the ambient light for both the near and far regions separately, which can effectively improve the brightness and color saturation of the restored image. Experiments performed in different scenes demonstrate that our method outperforms several state-of-the-art competitors in terms of efficiency and scene recovery performance.
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