低复杂度与抗误码的高光谱图像分布式压缩技术研究

项目名称： 低复杂度与抗误码的高光谱图像分布式压缩技术研究

项目编号： No.41201363

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 地理学

项目作者： 粘永健

作者单位： 中国人民解放军国防科学技术大学

项目金额： 22万元

中文摘要： 随着星载成像光谱仪的光谱分辨率、空间分辨率与辐射分辨率的不断提高，所获取的高光谱数据量急剧增加，必须研究高效的高光谱图像压缩技术，才能够在现有信道带宽条件下实现数据的实时传输。传统的基于联合编解码的压缩算法存在编码复杂度高与抗误码性能差的不足，难以有效应用于星载高光谱图像的压缩。为此，本项目深入研究低复杂度与抗误码的高光谱图像分布式压缩技术，利用多元陪集码与二元纠错码分别进行实现。在多元陪集码方面，研究高光谱图像的多元相关性估计以及相应的分布式无损压缩算法；研究分布式有损压缩中的率失真模型以及相应的压缩算法，使得高光谱图像在目标码率下获得理想的重建结果。在二元纠错码方面，研究高光谱图像的二元相关性估计以及相应的分布式压缩算法。最后，研究高光谱图像压缩质量评估算法，能够对压缩算法的性能进行全面客观的评估，并能推广到其它类型遥感图像的压缩质量评估。

中文关键词： 高光谱遥感；高光谱图像；无损压缩；有损压缩；分布式信源编码

英文摘要： With the increase of spectral resolution, spatial resolution and radiant resolution of on-board imaging spectrometer, the data volumes of acquired hyper-spectral images increase rapidly. Efficient compression technique of hyper-spectral images must be studied in order to realize the real-time transmission of data volumes under the existing channel bandwidth. The traditional compression algorithms based on joint encoding and decoding have the disadvantages of high encoder complexity and weak error resilience, which are difficult to be used for the on-board compression of hyper-spectral images effectively. Therefore, low complexity and error resilience distributed compression technique of hyper-spectral images is studied deeply in this project, which is realized by multilevel coset codes and binary error-correcting codes respectively. For multilevel coset codes, multilevel correlation estimation of hyper-spectral images and corresponding distributed lossless compression algorithms are studied, and the rate-distortion model of distributed lossy compression and corresponding compression algorithms are also studied, in order to obtain perfect reconstructed results of hyper-spectral images under the target rate. For binary error-correcting codes, binary correlation estimation of hyper-spectral images and corresponding

英文关键词： hyperspectral remote sensing；hyperspectral images；lossless compression；lossy compression；distributed source coding