空间相关性约束联合子空间追踪的高光谱图像稀疏解混
TP751; 通过深入分析高光谱图像空间相邻数据之间的空间相关性,提出一种利用空间相关性进行约束的联合子空间追踪解混(Spatial correlation constrained simultaneous subspace pursuit,SCCSSP)方法.该方法首先基于分块思想将高光谱图像进行分块处理,然后在图像块的端元提取步骤中,结合空间相关性特征对端元的提取进行约束,从而确保当前端元支撑集相对于高光谱图像残差是最优的.在丰度估计中将图像块的端元集合合并作为整幅图像的端元支撑集,通过求解非负性约束的最小二乘法获得丰度重建图像.模拟图像数据实验结果表明,本文方法在同等条件下能够获得更高的...
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| Published in | 南京航空航天大学学报 Vol. 51; no. 5; pp. 577 - 585 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
南京航空航天大学航天学院,南京,210016%南京航空航天大学无人机研究院,南京,210016
01.10.2019
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1005-2615 |
| DOI | 10.16356/j.1005-2615.2019.05.001 |
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| Abstract | TP751; 通过深入分析高光谱图像空间相邻数据之间的空间相关性,提出一种利用空间相关性进行约束的联合子空间追踪解混(Spatial correlation constrained simultaneous subspace pursuit,SCCSSP)方法.该方法首先基于分块思想将高光谱图像进行分块处理,然后在图像块的端元提取步骤中,结合空间相关性特征对端元的提取进行约束,从而确保当前端元支撑集相对于高光谱图像残差是最优的.在丰度估计中将图像块的端元集合合并作为整幅图像的端元支撑集,通过求解非负性约束的最小二乘法获得丰度重建图像.模拟图像数据实验结果表明,本文方法在同等条件下能够获得更高的信号重构误差,且解混运算时间低于凸优化算法.在实际图像数据实验中,本文方法丰度图像稀疏度最低,取得了仅次于SUnSAL-TV算法的图像重建误差,其所得到的丰度重建图像也取得了更好的视觉效果.实验结果验证了本文方法具有更高的解混精度. |
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| AbstractList | TP751; 通过深入分析高光谱图像空间相邻数据之间的空间相关性,提出一种利用空间相关性进行约束的联合子空间追踪解混(Spatial correlation constrained simultaneous subspace pursuit,SCCSSP)方法.该方法首先基于分块思想将高光谱图像进行分块处理,然后在图像块的端元提取步骤中,结合空间相关性特征对端元的提取进行约束,从而确保当前端元支撑集相对于高光谱图像残差是最优的.在丰度估计中将图像块的端元集合合并作为整幅图像的端元支撑集,通过求解非负性约束的最小二乘法获得丰度重建图像.模拟图像数据实验结果表明,本文方法在同等条件下能够获得更高的信号重构误差,且解混运算时间低于凸优化算法.在实际图像数据实验中,本文方法丰度图像稀疏度最低,取得了仅次于SUnSAL-TV算法的图像重建误差,其所得到的丰度重建图像也取得了更好的视觉效果.实验结果验证了本文方法具有更高的解混精度. |
| Author | 周永波 朱成 徐诚 孔繁锵 |
| AuthorAffiliation | 南京航空航天大学航天学院,南京,210016%南京航空航天大学无人机研究院,南京,210016 |
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| Author_FL | ZHU Cheng XU Cheng KONG Fanqiang ZHOU Yongbo |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DocumentTitle_FL | Spatial Correlation Constrained Simultaneous Subspace Pursuit for Sparse Unmixing of Hyperspectral Imagery |
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| Keywords | 贪婪算法 高光谱图像 稀疏解混 高光谱解混 多重测量向量 |
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| Publisher | 南京航空航天大学航天学院,南京,210016%南京航空航天大学无人机研究院,南京,210016 |
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| Title | 空间相关性约束联合子空间追踪的高光谱图像稀疏解混 |
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