Improved Rice Algorithm of Lossless Compression for On-Board Images
文献类型：会议论文
| 作者 | Wei YW(魏永旺) ; Ding QH(丁庆海); Luo HB(罗海波)
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| 出版日期 | 2010 |
| 会议名称 | 2010 International Conference on Multimedia Technology (ICMT) |
| 会议日期 | October 29-31, 2010 |
| 会议地点 | Ningbo, China |
| 关键词 | Lossless compression Rice algorithm MED Rowbased prediction Global unicode |
| 页码 | 5 pp. |
| 中文摘要 | Aiming at the problems of the relatively lower compression ratio and the difficulty in hardware implementation regarding Rice lossless compression algorithm for the Space-borne Remote-sensing images, an improved Rice method is proposed in which the length of predictor FIFO is determined by the size of input images and the global unicode for differences is used. The improved Rice algorithm is mainly composed of two steps, MED prediction for the whole row data and Rice global uniform entropy coding. The statistical results show that it can significantly reduce the spatial redundancy of the adjacent pixels and the mean value of image differences. The compression bit rate is reduced approximately 0.4581 bpp(bit/pixel) against the original Rice algorithm. Furthermore, the new way reserves the all detail information of the input images throughout the whole encoding process. Because we split the all samples with the same mode, the proportion of the identifier of the splitting mechanic in the output data stream is reduced and the compression ratio is increased. The improvement can reduce the encoding complexity and be easily implemented for hardware application. |
| 收录类别 | EI |
| 产权排序 | 1 |
| 会议录 | 2010 International Conference on Multimedia Technology (ICMT)
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| 会议录出版者 | IEEE |
| 会议录出版地 | Piscataway, NJ, USA |
| 语种 | 中文 |
| ISBN号 | 978-1-4244-7871-2 |
| 源URL | [http://ir.sia.cn/handle/173321/7987]  |
| 专题 | 沈阳自动化研究所_光电信息技术研究室 |
| 推荐引用方式 GB/T 7714 | Wei YW,Ding QH,Luo HB. Improved Rice Algorithm of Lossless Compression for On-Board Images[C]. 见:2010 International Conference on Multimedia Technology (ICMT). Ningbo, China. October 29-31, 2010. |
入库方式： OAI收割
来源：沈阳自动化研究所
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