自动化学报2011，Vol.37Issue(7)：820-827,8.DOI:10.3724/SP.J.1004.2011.00820
基于多尺度压缩感知金字塔的极化干涉SAR图像分类
PolInSAR Image Classification Based on Compressed Sensing and Multi-scale Pyramid
摘要
Abstract
In this paper, we propose a novel approach based on compressed sensing (CS) and multi-scale pyramid in synthetic aperture radar (SAR) image classification. Firstly, a multi-scale PolInSAR feature space is constructed by wavelet transform and feature extraction on the original image; then, CS provides a transform for the measurement domain and recovers the sparse features in the data domain on the image patches in each scale; finally, the combination of multi-scale sparse features generates the final multi-scale pyramid representation of the image for classification. Motivated by the limitations of sparse coding and general pyramid methods, we not only take the advantages of observation matrix in dimension reduction, but also perform analysis on texture features in different scales. Experimental results on the first batch of PolInSAR data show the presented approach's efficiency.关键词
图像处理/合成孔径雷达/图像分类/压缩感知/多尺度金字塔Key words
Image processing/ synthetic aperture radar (SAR)/ image classification/ compressed sensing (CS)/ multi-scale pyramid引用本文复制引用
何楚,刘明,冯倩,邓新萍..基于多尺度压缩感知金字塔的极化干涉SAR图像分类[J].自动化学报,2011,37(7):820-827,8.基金项目
国家重点基础研究发展计划(973计划)(2007CB714405),国家自然科学基金(60702041),测绘遥感信息工程国家重点实验室专项科研经费资助 （973计划）
