摘要
基于Shannon采样定理的传统信息获取系统在高空间、时间和谱分辨率及系统其它性能上存在难以突破的瓶颈,压缩采样理论为提升航天遥感信息获取能力提供了新的思路。基于压缩采样理论的成像技术(压缩成像)将采样、压缩和数据处理3个过程完美的结合在一起,避免了传统遥感成像系统"先采样再压缩"方式带来的传感器和计算资源浪费,是未来光学遥感极具潜力的成像方式。文章在简要介绍压缩采样基本理论的基础上,总结和分析了国际上目前提出的光学压缩成像系统原型,设计开展了3组压缩成像物理实验,特别结合航天遥感需求设计了推扫式压缩成像方案,实验结果验证了压缩采样的基本原理,并为未来光学遥感压缩成像系统的设计提供了借鉴。
Compressive sampling provides a new way for increasing the capability of information acqui-sition. Compressive sampling asserts that it is possible to accurately reconstruct signals from sub-Nyquist sam-pling, provided we make some additional assumptions(sparse or compressible) about the signal in question. The compressive imaging technology, which is based on the compressive sampling theory, integrates the proc-esses of sampling, compression and processing perfectly, avoiding resource waste caused by a traditional“sam-ple-then-compress”mode, and is a potential imaging technique for optical remote sensing. This paper first re-views the basic theory of compressive sampling. Then, several optical compressive imaging systems are intro-duced. Finally three physical experiments are designed to validate the principle of compressive imaging and the experiment results can be used as reference for the future optical remote compressive imaging system.
出处
《航天返回与遥感》
2014年第1期54-62,96,共10页
Spacecraft Recovery & Remote Sensing
基金
国家自然科学基金项目(61002024)资助
关键词
压缩采样
压缩成像
稀疏表示
测量矩阵
空间遥感
compressive sampling
compressive imaging
sparse representation
measurement matrix
space remote sensing