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Absolute Depth Estimation from a Single Defocused Image
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DOI：10.1109/TIP.2013.2274389.png)
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摘要
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Shape from defocus (SFD) is one of the most popular techniques in monocular 3D vision. While most SFD approaches require two or more images of the same scene captured at a fixed view point, this paper presents an efficient approach to estimate absolute depth from a single defocused image. Instead of directly measuring defocus level of each pixel, we propose to design a sequence of aperture-shape filters to segment a defocused image by defocus level. A boundary-weighted belief propagation algorithm is employed to obtain a smooth depth map. We also give an estimation of depth error. Extensive experiments show that our approach outperforms the state-of-the-art single-image SFD approaches both in precision of the estimated absolute depth and running time.
Keyword:
Shape from defocus
monocular 3D vision
aperture-shape filters
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期刊
IF:
13.7
论文数:
1.0W
被引数:
8.4W
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