15 October 2012 Depth estimation based on adaptive support weight and SIFT for multi-lenslet cameras
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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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuan Gao, Yuan Gao, Wenjin Liu, Wenjin Liu, Ping Yang, Ping Yang, Bing Xu, Bing Xu, } "Depth estimation based on adaptive support weight and SIFT for multi-lenslet cameras", 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; https://doi.org/10.1117/12.975694

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