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
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI