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首页> 外文期刊>Pattern Analysis and Machine Intelligence, IEEE Transactions on >Removal of Partial Occlusion from Single Images
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Removal of Partial Occlusion from Single Images

机译：从单个图像中去除部分遮挡

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摘要

This paper examines large partial occlusions in an image which occur near depth discontinuities when the foreground object is severely out of focus. We model these partial occlusions using matting, with the alpha value determined by the convolution of the blur kernel with a pinhole projection of the occluder. The main contribution is a method for removing the image contribution of the foreground occluder in regions of partial occlusion, which improves the visibility of the background scene. The method consists of three steps. First, the region of complete occlusion is estimated using a curve evolution method. Second, the alpha value at each pixel in the partly occluded region is estimated. Third, the intensity contribution of the foreground occluder is removed in regions of partial occlusion. Experiments demonstrate the method's ability to remove the effects of partial occlusion in single images with minimal user input.
机译：本文研究了当前景物体严重失焦时在深度不连续附近出现的图像中的大局部遮挡。我们使用遮罩对这些部分遮挡进行建模，其alpha值由模糊核与封堵器的针孔投影的卷积确定。主要的贡献是一种用于去除部分遮挡区域中前景遮挡物的图像贡献的方法，该方法可以改善背景场景的可见性。该方法包括三个步骤。首先，使用曲线演化方法估计完全遮挡的区域。其次，估计部分被遮挡区域中的每个像素处的α值。第三，在部分阻塞的区域中消除了前景阻塞器的强度贡献。实验表明，该方法可以用最少的用户输入消除单个图像中部分遮挡的影响。

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