Ebook: Hyperspectral Image Processing
Author: Wang L. Zhaj C.
- Genre: Computers // Organization and Data Processing
- Tags: Информатика и вычислительная техника, Обработка медиа-данных, Обработка изображений
- Language: English
- pdf
Springer, 2016. — 327 p.With the rapid development of the modern science and technology, the hyperspectral remote sensing science, as a comprehensive high and new technology, has gained the extensive as well as considerable development in the theory, technology, and application. The hyperspectral remote sensing will acquire the land object information by utilizing the space image and spectral features, to achieve the unity of image and spectrum and provide the powerful technical support for the humans to learn the world and change the world. At present, the hyperspectral remote sensing has been widely applied to the fields such as military affairs, agriculture, forest, meadow, ocean, geology, and ecology. In recent years, the quantity of the remote sensing SCI periodicals and the impact factors have been increased internationally, and the international academic conference specially aiming at the hyperspectrum is gradually developed and continues to mature.
The development degree of the hyperspectral image processing technique directly determines the information acquisition and utilization degree. Our country attaches importance to the development of this technique. The supporting strength of the fields involving 863, 973, and Natural Science Foundation of China is bigger and bigger, and the human powers input by various national colleges and universities and the scientific research institutions are more and more, with more and more abundant achievements. However, this current situation still cannot meet the demands of the scholars on the breadth and depth of the technique. In combination with the research of the author engaging in the related technique for many years, this book carries out the systematic classification and elaborate interpretation for the main processing techniques of hyperspectral remote sensing, i.e., classification, endmember extraction, spectral unmixing, sub-pixel mapping, super-resolution reconstruction, anomaly detection, dimensionality reduction, and the newer research results, for the purpose of contributing the small gains for the readers to understand, learn, and research the hyperspectral image processing technique.Basic Theory and Main Processing Techniques of Hyperspectral Remote Sensing.
Classification Technique for HSI.
Endmember Extraction Technique of HSI.
Spectral Unmixing Technique of HSI.
Subpixel Mapping Technique of HSI.
Super-Resolution Technique of HSI.
Anomaly Detection Technique of HSI.
Dimensionality Reduction and Compression Technique of HSI.
Introduction of Hyperspectral Remote Sensing Applications.
The development degree of the hyperspectral image processing technique directly determines the information acquisition and utilization degree. Our country attaches importance to the development of this technique. The supporting strength of the fields involving 863, 973, and Natural Science Foundation of China is bigger and bigger, and the human powers input by various national colleges and universities and the scientific research institutions are more and more, with more and more abundant achievements. However, this current situation still cannot meet the demands of the scholars on the breadth and depth of the technique. In combination with the research of the author engaging in the related technique for many years, this book carries out the systematic classification and elaborate interpretation for the main processing techniques of hyperspectral remote sensing, i.e., classification, endmember extraction, spectral unmixing, sub-pixel mapping, super-resolution reconstruction, anomaly detection, dimensionality reduction, and the newer research results, for the purpose of contributing the small gains for the readers to understand, learn, and research the hyperspectral image processing technique.Basic Theory and Main Processing Techniques of Hyperspectral Remote Sensing.
Classification Technique for HSI.
Endmember Extraction Technique of HSI.
Spectral Unmixing Technique of HSI.
Subpixel Mapping Technique of HSI.
Super-Resolution Technique of HSI.
Anomaly Detection Technique of HSI.
Dimensionality Reduction and Compression Technique of HSI.
Introduction of Hyperspectral Remote Sensing Applications.
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