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Layered perceptual representation for shadow vision: From detection to removal

机译:阴影视觉的分层感知表示:从检测到去除

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摘要

On the research of shadow essence and visual scheme, we propose a single image shadow removal method based on certain layered perceptual representation models with the flowchart from shadow detection to shadow removal. Firstly, a modified intersecting cortical model, the typically useful image factorization technique, is applied to extract umbra and penumbra masks. Then, under the energy minimization framework, scale factors for umbra are computed. Furthermore, transparency-coupled atmospheric transfer function is introduced for penumbra compensation by pixel-by-pixel transparency estimation. For aerial images, experimental results illustrate that shadow regions are matted well, and the proposed method yields vivid shadow-free images with smooth boundaries.
机译:在对阴影本质和视觉方案的研究中,我们提出了一种基于某些分层感知表示模型的单图像阴影去除方法,并给出了从阴影检测到阴影去除的流程图。首先,将改进的相交皮质模型(通常有用的图像分解技术)应用于提取本影和半影蒙版。然后,在能量最小化框架下,计算本影的比例因子。此外,引入了透明度耦合的大气传递函数,用于通过逐像素的透明度估计进行半影补偿。对于航空图像,实验结果表明阴影区域可以很好地消光,并且所提出的方法可生成具有平滑边界的生动的无阴影图像。

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