cs.AI updates on arXiv.org 07月04日 12:08
Illuminant and light direction estimation using Wasserstein distance method
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本文提出一种基于Wasserstein距离的图像光照估计方法,通过实验证明其在复杂光照环境下优于传统方法,适用于光源定位、图像质量评估和物体检测增强。

arXiv:2503.05802v2 Announce Type: replace-cross Abstract: Illumination estimation remains a pivotal challenge in image processing, particularly for robotics, where robust environmental perception is essential under varying lighting conditions. Traditional approaches, such as RGB histograms and GIST descriptors, often fail in complex scenarios due to their sensitivity to illumination changes. This study introduces a novel method utilizing the Wasserstein distance, rooted in optimal transport theory, to estimate illuminant and light direction in images. Experiments on diverse images indoor scenes, black-and-white photographs, and night images demonstrate the method's efficacy in detecting dominant light sources and estimating their directions, outperforming traditional statistical methods in complex lighting environments. The approach shows promise for applications in light source localization, image quality assessment, and object detection enhancement. Future research may explore adaptive thresholding and integrate gradient analysis to enhance accuracy, offering a scalable solution for real-world illumination challenges in robotics and beyond.

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光照估计 图像处理 Wasserstein距离 机器人
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