Abstract
We propose a low-complexity algorithm for stereoscopic video applications that generates a high-quality 3D image depth map from a single 2D image. Based on their characteristics, 2D images are classified into one of three categories before being processed by the proposed low-complexity algorithm to generate corresponding depth maps. We also extend the 3D depth algorithm to construct a parallel 3D video system. A thread-level superscalar-pipelining approach is developed to parallelize the 3D video system. Experimental results for HD1080 resolution images demonstrate that the algorithm can generate high-quality depth maps with an average reduction in the computational complexity of 98.2 % compared with a conventional algorithm. The parallel 3D video system can achieve a processing speed of 63.66 fps for HD720 resolution video.
Original language | English |
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Pages (from-to) | 17-33 |
Number of pages | 17 |
Journal | Journal of Signal Processing Systems |
Volume | 72 |
Issue number | 1 |
DOIs | |
State | Published - 1 Jul 2013 |
Keywords
- 3D image/video
- Depth map
- Parallel computing
- Stereo