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机构地区:[1]西北工业大学电子信息学院,陕西西安710129 [2]铜陵学院电气工程系,安徽铜陵244000
出 处:《光学精密工程》2014年第11期3129-3135,共7页Optics and Precision Engineering
基 金:国家自然科学基金资助项目(No.61071171);安徽省高等学校省级自然科学研究基金资助项目(No.KJ2013B298);西北工业大学博士论文创新基金资助项目(No.CX201424)
摘 要:提出一种推扫式谱间压缩采样的高光谱成像系统,用于实现高光谱图像的压缩感知成像,并对该系统成像的重构算法进行了研究。在图像采集阶段,采用棱镜对地面成像行的像素进行谱带分离,然后利用数字微镜器件实现谱带的线性编码,通过柱面透镜完成编码谱带的叠加。压缩采样数据重构时,不像传统的压缩感知重构方法那样直接重构高光谱数据,而是利用线性光谱库混合模型将重构高光谱数据转换成重构丰度系数矩阵,采用交替方向乘子法求解丰度的优化问题,再根据重构的丰度和高光谱库恢复原数据。与标准压缩感知重构算法的对比实验表明,该方法在压缩采样数据为总数据的20%时,重构的平均峰值信噪比比标准压缩感知提高了18dB。所设计的成像系统采样方式简单,可应用于星载或机载的高光谱压缩感知成像。A pushbroom spectral imaging system based on compressive sampling was established to realize compressive sensing imaging for a hyperspectral image.An image reconstruction algorithm for this system was investigated.In the image acquisition stage,the pixels of ground imaging line were separated along spectral direction by a prism.Then,the linear encoding between the spectral bands was realized by a digital micro-mirror device.Finally,the encoded spectral bands were summed by a cylindrical lens.In the reconstruction of the compressive sampled data,the traditional compressive sensing reconstruction methods which recover hyperspectral data directly were abandoned.The liner spectral library mixed models were used to convert the reconstructed hyperspectral data into reconstructed abundance fraction matrix,the alternating direction method of multipliers was used to solve the optimizing problem of abundance,and the data was recovered by using the reconstructed abundance and spectral library.The comparison experiment between standard compressive sensing reconstruction and our algorithm shows that the reconstructed average peak signal noise rate of our algorithm is improved about 18 dB than that of the standard compressive sensing when the used data are 20% that of total data.The system is suitable for the spaceborne airborne hyperspectral compressive sensing imaging for its simple sampling.
关 键 词:压缩感知 高光谱图像 成像光谱仪 线性混合模型 感知矩阵
分 类 号:TP75[自动化与计算机技术—检测技术与自动化装置]
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