深度从散焦和模糊的单一图像

Huadong Sun, Zhijie Zhao, Xuesong Jin, Lianding Niu, Lizhi Zhang
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引用次数: 4

摘要

单幅图像的深度问题是计算机视觉中的一个热点问题,它对二维/三维图像的转换具有重要意义。一般来说,景物的深度随离焦图像的模糊程度而变化。因此,景深可以通过测量模糊来恢复。本文提出了一种基于聚焦/离焦线索的深度估计新方法,该方法以小波分解的高频子带熵作为模糊度量。该方法不需要选择阈值,可以提供像素级深度图。实验结果表明,该方法是有效可靠的。
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Depth from defocus and blur for single image
Depth for single image is a hot problem in computer vision, which is very important to 2D/3D image conversion. Generally, depth of the object in the scene varies with the amount of blur in the defocus images. So, depth in the scene can be recovered by measuring the blur. In this paper, a new method for depth estimation based on focus/defocus cue is presented, where the entropy of high frequency subband of wavelet decomposition is regarded as the measure of blur. The proposed method, which is unnecessary to select threshold, can provide pixel-level depth map. The experimental results show that this method is effective and reliable.
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