| dc.contributor.author | Wong, Kit Sai | |
| dc.date.accessioned | 2014-09-29T19:41:49Z | |
| dc.date.available | 2014-09-29T19:41:49Z | |
| dc.date.issued | 1997-05-01 | |
| dc.identifier.uri | https://hdl.handle.net/11244/12421 | |
| dc.description.abstract | Arabnia's process-and-data-decomposition approach can be applied to many image processing jobs other than image rotation. I have developed a generalized topology for image processing. I investigate the efficiency. speed-up of the generalized topology and the factors which affect the performance of the generalized topology. But the generalized topology has a drawback, it is not load balanced in most cases. So I further develop a linked-trees topology with better load balance capability. And the performances such as efficiency and speed-up of the linked-trees topology are investigated. And I analyze the factors affecting these performances. In conclusion, the linked-trees topology is superior in time efficiency and speed-up than the generalized topology. | |
| dc.format | application/pdf | |
| dc.language | en_US | |
| dc.publisher | Oklahoma State University | |
| dc.rights | Copyright is held by the author who has granted the Oklahoma State University Library the non-exclusive right to share this material in its institutional repository. Contact Digital Library Services at lib-dls@okstate.edu or 405-744-9161 for the permission policy on the use, reproduction or distribution of this material. | |
| dc.title | Processor Topologies for Image Processing Applications | |
| dc.type | text | |
| osu.filename | Thesis-1997-W872p.pdf | |
| osu.accesstype | Open Access | |
| dc.type.genre | Thesis | |
