General 3D stereo vision is composed of two major phases. In the first phase, an image and its corresponding depth map are generated using stereo matching. In the second phase, depth-based image rendering (DIBR) is employed to generate images of different view angles. Stereo matching, a computation-intensive operation, generates the depth maps from two images captured at two different view positions. In this thesis, we present hardware designs of three different stereo matching methods: pixel-based, window-based, and dynamic programming (DP)-based. Pixel--based and window-based methods belong to the local optimization stereo matching methods while DP, one of the global optimization methods, consists of three main processing steps: matching cost computation, cost aggregation, and back-tracing. Hardware implementation of DP-based stereo matching usually requires large memory space to store the intermediate results, leading to large area cost. In this thesis, we propose a tile-based DP method by partition the original image into smaller tiles so that the processing of each tile requires smaller memory size.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0808111-103145 |
| Date | 08 August 2011 |
| Creators | Wang, Ying-Chung |
| Contributors | Chen Chung-Ho, Shen-Fu Hsiao, Yun-Nan Chang, Shiann-Rong Kuang, Ming-Chih Chen |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0808111-103145 |
| Rights | user_define, Copyright information available at source archive |
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