遥感影像混合像元分解及超分辨率重建研究进展
Mixed-pixel Decomposition and Super-resolution Reconstruction of RS Image
查看参考文献62篇
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文摘
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随着遥感应用的深入, 传统将遥感影像像元当作纯净像元的方式所带来的问题已经被广泛认识到, 混合像元分解的相关理论和技术成为遥感领域的一个热点问题。本文总结了混合像元分解及超分辨率影像重建的主要理论和方法。根据超分辨率影像重建的主要流程, 分别回顾了混合像元端元类型选择、端元丰度分解和超分辨率影像的重建, 并对相关模型和技术给出了总结和评价。端元类型选择是确定在影像范围包含的纯净地物类型, 重点介绍了基于统计学和几何学的两种方法。端元丰度估计是目前该领域研究最多的方向之一, 集中了很多新的理论和方法, 可变端元分解和盲源分解作为2种效果较好的方法在文中作了详细的回顾和评价。空间自相关性是对丰度估计的结果进行超分辨率重建的主要理论基础, 如何在丰度约束条件下最大化空间自相关性是大多数基于混合像元分解超分辨率重建的目标。最后, 文章在总结目前混合像元分解及超分辨率遥感影像理论发展的基础上, 给出了一些意见和展望, 指出考虑混合像元形成机理、综合多种模型及先验信息将有助于基于混合像元分解的超分辨率遥感影像研究。 |
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其他语种文摘
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Remote sensing technology has been used in a wide range of applications,but the mixed-pixel phenomenon has been a persistent problem.In traditional classification,every pixel is considered a pure pixel and can be classified as only one type. This affects the accuracy and precision of results in applications. Recently,the problem has been studied by many researchers who have adopted many models and methods to decompose mixed-pixels and reconstruct super-resolution images from the low-resolution originals.In this article,we give a literature review of the development of mixed-pixel decomposition and super-resolution reconstruction.In accord with the main flow in the process,three aspects are reviewed:(1)endmember selection,(2)abundance estimation,and(3)super-resolution reconstruction. Endmember selection aims at selecting pure objects in the whole image range. Statistical methods and geometrical methods have been covered in detail for endmember selection. Abundance estimation of endmembers in pixels is another vital step attracting a great deal of research.It involves a number of new models and methods.We put an emphasis on variable endmember spectral mixture analysis and blind sources separation methods,which perform well and seem promising. Super-resolution reconstruction is based on the result of abundance estimation. How to maximize the spatial auto-correlation is the main objective when reconstructing super-resolution images.We review the most commonly used pixel-swapping method at length and discuss some problems presented in the study. Finally,some suggestions are brought forward for the mixed-pixel decomposition and super-resolution reconstruction of RS images. |
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来源
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地理科学进展
,2010,29(6):747-756 【核心库】
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关键词
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端元选择
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丰度估计
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盲源分解
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混合像元分解
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超分辨率重建
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地址
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中国科学院地理科学与资源研究所, 中国科学院资源与环境信息系统国家重点实验室, 北京, 100101
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语种
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中文 |
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文献类型
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综述型 |
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ISSN
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1007-6301 |
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学科
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自然地理学 |
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基金
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国家自然科学基金
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国家863计划
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国家科技部国际合作项目
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中国科学院知识创新工程项目
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文献收藏号
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CSCD:3902182
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