Abstract
This paper presents an efficient joint disparity-motion estimation algorithm and fast estimation scheme for stereo sequence CODEC. In stereo sequences, frames from one camera view (usually the left) are defined as the base layer, and frames from the other one as the enhancement layer. The enhancement-from-base-layer prediction then turns out as a disparity-compensated prediction instead of a motion-compensated prediction. Although the disparity-compensated prediction fails, it is still possible to achieve compression by motion-compensated prediction with the same channel. At the same time, the base layer represents a monoscopic sequence. Joint disparity-motion estimation can increase coding efficiency and reduce complexity of stereo CODEC using relationship between disparity and motion fields. The disparity vectors are estimated by using the left and right motion vectors and the previous disparity vectors in each time frame. In order to obtain more accurate disparity vectors, we include spatial prediction process after joint estimation. From joint estimation and spatial prediction, we can obtain accurate disparity vectors and then increase coding efficiency. Moreover, we proposed fast motion estimation technique which utilizes correlation for motion vectors of neighboring blocks. We confirmed PSNR of the proposed method increases by 0.5-1.5dB compared to the conventional methods from simulation results. At the same time, the processing time is reduced by almost 1/10.
Original language | English |
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Article number | 94 |
Pages (from-to) | 833-842 |
Number of pages | 10 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 5685 |
Issue number | PART 2 |
DOIs | |
Publication status | Published - 2005 |
Event | Proceedings of SPIE-IS and T Electronic Imaging - Image and Video Communications and Processing 2005 - San Jose, CA, United States Duration: 2005 Jan 18 → 2005 Jan 20 |
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering