| 高光谱图像处理与信息提取前沿 |
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| 引用本文： | 张兵.高光谱图像处理与信息提取前沿[J].遥感学报,2016,20(5):1062-1090. |
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| 作者姓名： | 张兵 |
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| 作者单位： | 中国科学院遥感与数字地球研究所 数字地球重点实验室, 北京 100094 |
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| 基金项目： | 国家杰出青年科学基金（编号：41325004） |
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| 摘 要： | 高光谱遥感是对地观测的重要手段,高光谱图像处理与信息提取技术则是高光谱遥感领域的核心研究内容之一。本文简要介绍了高光谱遥感的主要特点,系统梳理了高光谱图像处理与信息提取面临的关键问题和主要研究方向,在此基础上,从噪声评估与数据降维方法、混合像元分解方法、图像分类方法、目标探测与异常探测方法等4个方面对高光谱图像处理与信息提取的理论发展过程和最新前沿进展进行了综述。另外,还对高光谱图像处理与信息提取中的高性能处理技术进行了总结和分析。未来,伴随着智能化信息分析和高性能硬件处理技术发展,高光谱遥感卫星系统也将步入智能化时代。针对这一趋势,本文指出高光谱图像处理与信息提取方法要注重多学科交叉,充分利用机器学习、人工智能等领域的新成果;要重视软硬件结合,发展高光谱图像高性能实时处理技术;要紧密结合应用需求,发挥高光谱遥感的优势和特点,发展新理论和新方法。
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| 关 键 词： | 高光谱遥感 数据降维 混合像元分解 图像分类 目标探测 高性能计算 |
| 收稿时间： | 2016/6/15 0:00:00 |
| 修稿时间： | 2016/7/15 0:00:00 |
Advancement of hyperspectral image processing and information extraction |
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| ZHANG Bing.Advancement of hyperspectral image processing and information extraction[J].Journal of Remote Sensing,2016,20(5):1062-1090. |
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| Authors: | ZHANG Bing |
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| Institution: | Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China |
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| Abstract: | Hyperspectral remote sensing is an important technique in Earth observation. Hyperspectral image processing and information extraction is one of the key issues in hyperspectral remote sensing. This paper introduces the major characteristics of hyperspectral remote sensing. It also summarizes and reviews the development history and current advancements of hyperspectral image processing and information extraction, which mainly comprises four aspects:data dimensionality reduction, pixel unmixing, image classification, and target and anomaly detection. Moreover, the high-performance computing technique in hyperspectral image processing and information extraction is summarized and analyzed. In the future, the technical developments of intelligent information analysis and high-performance processing based on hardware indicate that the hyperspectral remote sensing satellite system will enter an intelligent era. Therefore, the present studyindicates three aspects that should be considered in hyperspectral image processing and information extraction. First, a multidisciplinary connection should be emphasized, and new achievements in the fields of machine learning and artificial intelligence should be fully adopted. Second, close attention should be given to the integration of software and hardware to develop a high-performance technique for processing hyperspectral images in real time. Finally, the advantages and characteristics of hyperspectral remote sensing should be extensively explored, and the development of new theories and new methods should integrate the requirements of various applications. |
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| Keywords: | hyperspectral remote sensing data dimensionality reduction pixel unmixing image classification target detection high performance computing |
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