Real-time imagery compression method research
文献类型：会议论文
| 作者 | Maotang Li ; Jingbo Guo ; Jinping Zhao ; Yuzhong Liu |
| 出版日期 | 2003 |
| 会议名称 | Conference on Ocean Remote Sensing and Imaging II |
| 会议日期 | 2003 |
| 会议地点 | San Diego, Ca |
| 关键词 | real-time communication image compression ocean monitor wavelet-based algorithm |
| 页码 | 531-539 |
| 通讯作者 | 北京8701信箱 |
| 英文摘要 | A very useful Real-Time Ocean Surveying System (RTOSS) has been developing. Because of the real-time transmission and the huge synthesize aperture radar (SAR) imagery data and video imagery data and because of the restricted communication channel and the limited transmitting power condition the image data compression methods have to be developed. The compressed SAR imagery data and video imagery data have to satisfy two conditions: One is the excellent quality reconstruction; another is that the system can work on the real-time operating condition. It is contradictory for the excellent quality reconstruction with the real time system operation. In order to satisfy the real-time operating condition, the wavelet-based SAR imagery and improved H.263-based video imagery compression algorithms have been developed, which is of a high compression multiples and tiny compression distortion. In this paper, several typical SAR imagery compression algorithms are introduced and their performances and practical feasibility are compared. Secondly, the developed compression software that adopts improved H.263-based video imagery methods will be introduced. Finally, some experiment results will be given. |
| 收录类别 | CPCI |
| 会议网址 | |
| 会议录 | Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie)
 |
| 会议录出版者 | Spie-Int Soc Optical Engineering |
| 学科主题 | 空间技术 |
| 会议录出版地 | BELLINGHAM |
| 语种 | 英语 |
| ISSN号 | 0277-786X |
| ISBN号 | 0-8194-5024-3 |
| 源URL | [http://ir.cssar.ac.cn/handle/122/1636]  |
| 专题 | 国家空间科学中心_其他部室 |
| 推荐引用方式 GB/T 7714 |
Maotang Li,Jingbo Guo,Jinping Zhao,et al. Real-time imagery compression method research[C]. 见:Conference on Ocean Remote Sensing and Imaging II. San Diego, Ca. 2003. |
入库方式： OAI收割
来源：国家空间科学中心
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