基于线性规划感知的压缩高光谱遥感图像快速重建

项目名称： 基于线性规划感知的压缩高光谱遥感图像快速重建

项目编号： No.61501334

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 无线电电子学、电信技术

项目作者： 石文轩

作者单位： 武汉大学

项目金额： 19万元

中文摘要： 随着高光谱遥感图像的谱段数量和采集速率不断提高，如何通过探索新的编码技术减轻图像采集端的负荷以及新的解码技术对图像进行快速重建，受到了研究者的关注。我们的前期工作发现，压缩感知理论为高光谱遥感图像的快速压缩带来了重大突破，但是该类图像的重建一直没有一种既快速又精确的方法。本项目以遥感高光谱图像为研究对象，项目的主要研究内容包括（1）利用谱段之间的预测残差比图像本身在变换域下更稀疏的特点，对谱段之间的预测残差建立数学重建模型。（2）研究线性规划与二次规划之间的等价关系，综合线性规划重建精度高和二次规划重建速度快的优势，将预测残差线性规划的重建问题转换为等价的二次规划重建问题。（3）联合相位相关和仿射变换方法进行各谱段图像配准，解决因轨道偏移等因素引起的像元匹配误差。本项目就是研究如何利用这种方法快速重建并配准所有谱段的遥感图像，提高图像的利用价值，从而为高光谱遥感图像的后续应用奠定基础。

中文关键词： 高光谱图像压缩；稀疏编码；压缩感知；线性规划；二次规划

英文摘要： With the incensement of spectral number and acquisition rate, how to exploit new coding technologies to release the load of acquisition end and new decoding methods to reconstruct images fast becomes challenging. In our earlier work, we found that compressed sensing theory brings a significant breakthrough for the rapid compression of the hyperspectral remote sensing images. However, there has not been a fast and accurate method for the reconstruction of such images. In this project, the hyperspectral remote sensing images are selected as the research object. The main contents include: (1) making use of the fact that prediction residual between spectral is more sparse than the image itself in transform domain, building the reconstruction model for the prediction residual between spectral; (3) researching the relationship between linear programming and quadratic programming, combining the high accuracy of linear programming and speed advantage of quadratic programming, converting the linear programming reconstruction for prediction residual to an equivalent quadratic programming reconstruction problem. Thereby, we can promote the speed of the reconstruction in the premise of ensuring the accuracy of the reconstruction; (3) proposing image registration method for each spectrum by phase correlation and affine transformation, which can obtain the registration error cause by orbit offset. This project will study how to use this method to quickly rebuild all spectral remote sensing images, and promote the value of the images. Thereby, we can build a foundation for the subsequent applications of hyperspectral remote sensing images.

英文关键词： Hyperspectral image compression;Sparse coding;Compressed sensing;Linear programming;Quadratic programming