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Proceedings Paper

Depth estimation based on adaptive support weight and SIFT for multi-lenslet cameras
Author(s): Yuan Gao; Wenjin Liu; Ping Yang; Bing Xu
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Paper Abstract

With a multi-lenslet camera, we can capture multiple low resolution subimages of the same scene and use them to reconstruct a high resolution image. The spatially variant shifts estimation between subimages is one of major problems. In this paper, a depth estimation algorithm has been proposed for multi-lenslet cameras. The stereo matching between the reference subimage and other subimages using segmentation-based Adaptive Support-Weight approach combined with Scale Invariant Feature Transform (SIFT) is introduced, which has an influence on the result of stereo matching. Then, disparity maps are converted to depth maps and these depth maps are merged into one map for quality improvement. At last, the average blending images at difference depth are calculated according to the depth map. The experimental results show that the proposed algorithm can extract accurate depth more concisely and efficiently.

Paper Details

Date Published: 15 October 2012
PDF: 4 pages
Proc. SPIE 8419, 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Sensing, Imaging, and Solar Energy, 84190C (15 October 2012); doi: 10.1117/12.975694
Show Author Affiliations
Yuan Gao, Institute of Optics and Electronics (China)
Key Lab. on Adaptive Optics (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Wenjin Liu, Institute of Optics and Electronics (China)
Key Lab. on Adaptive Optics (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Ping Yang, Institute of Optics and Electronics (China)
Key Lab. on Adaptive Optics (China)
Bing Xu, Institute of Optics and Electronics (China)
Key Lab. on Adaptive Optics (China)


Published in SPIE Proceedings Vol. 8419:
6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Sensing, Imaging, and Solar Energy
Yadong Jiang; Junsheng Yu; Zhifeng Wang, Editor(s)

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