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| 基于比特平面SBI变换的遥感图像无损压缩 | |
| 引用本文： | 苏东卫,慈林林,陈晓峰.基于比特平面SBI变换的遥感图像无损压缩[J].北京理工大学学报,2005,25(9):765-768. |
| 作者姓名： | 苏东卫 慈林林 陈晓峰 |
| 作者单位： | 1. 北京理工大学,信息科学技术学院计算机科学工程系,北京,100081 2. 北京理工大学,信息科学技术学院计算机科学工程系,北京,100081;信息高技术研究所,北京,100085 3. 信息高技术研究所,北京,100085 |
| 基金项目： | 国家高技术研究发展计划(863计划) |
| 摘 要： | 提出一种基于子块互换(subblock interchange,SBI)的遥感图像无损压缩方案.采用小波变换对遥感图像进行分解,将生成的频域数据按不同比特平面分别进行SBI变换并用算术编码进行压缩.该方案改进了基于列的扫描方式,将小波系数按幅值大小进行重新排序,根据SBI变换后数据特点取消了文本压缩中常用的前移编码(MTF),在降低复杂度的前提下提高了压缩率,同时具有信噪比和分辨率可扩展特性. |
| 关 键 词： | 遥感图像 比特平面编码 BWT算法 SBI变换 排序顺序 比特平面 变换对 遥感图像无损压缩 Plane Based Image Compression Remote Sensing 扩展特性 分辨率 信噪比 压缩率 前提 低复杂度 算术编码 前移 文本压缩 数据特点 重新排序 大小 小波系数 |
| 文章编号： | 1001-0645(2005)09-0765-04 |
| 收稿时间： | 11 10 2004 12:00AM |
| 修稿时间： | 2004年11月10日 |
Lossless Remote Sensing Image Compression Based on Subblock Interchange in Bit Plane |
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| SU Dong-wei,CI Lin-lin and CHEN Xiao-feng.Lossless Remote Sensing Image Compression Based on Subblock Interchange in Bit Plane[J].Journal of Beijing Institute of Technology(Natural Science Edition),2005,25(9):765-768. | |
| Authors: | SU Dong-wei CI Lin-lin and CHEN Xiao-feng |
| Institution: | 1. Department of Computer Science and Engineering, School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China; 2. Institute of Information High-Technology, Beiiing 100085, China |
| Abstract: | A lossless remote sensing image compression method based on subblock interchange (SBI) was presented. Remote sensing image was decompressed into frequency domain image by wavelet transform and the bit planes in frequency domain image were permuted by SBI transform seperately. The resulting data was compressed by arithmetic encoder. In the method, the column-based scan mode was improved, wavelet coefficients were resorted in magnitude order, MTF (move to front) code, which was often used in text compression method, was cancelled. The method achieves better compression performance and lower complexity. At the same time the method achieves desired feature of PSNR scalability and resolution scalability. |
| Keywords: | remote sensing image bit plane encoding Burrows-Wheeler transformation subblock interchange sorting order |
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