Fully unsupervised hyperspectral image analysis /
Ahmed Mohamed Ahmed Saied Elsheikh
Fully unsupervised hyperspectral image analysis / تحليل مكتمل بغير إشراف لصور الطيف الفائق Ahmed Mohamed Ahmed Saied Elsheikh ; Supervised Mohamed H. Farouk - Cairo : Ahmed Mohamed Ahmed Saied Elsheikh , 2014 - 113 P. : facsimiles ; 30cm
Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Mathematics and Physics
Spectroscopy is the study of light as a function of wavelength that has been emitted, reflected or scattered from a solid, liquid, or gas. Each material has its own spectral signature, and hence can be identified using spectral analysis. Hyperspectral imaging (HSI) - also called Imaging spectroscopy- sensors observe hundreds or thousands of contiguous spectral bands as well as spatial locality. A hyperspectral image cube (two spatial dimensions and the third is the wavelength) contains a large amount of information about the imaged scenario. Thus the automated analysis of such image cubes is an important asset. Spatial analysis in HSI is rather difficult due to the fact that HSI taken by a satellite or an airborne camera has low ground sampling distance (GSD). This means that many targets of interest can be located within one pixel. Another related problem is the availability of materials in nature as mixtures. As a result, spectral analysis is of great interest specially sub-pixel detection algorithms and spectral unmixing
Endmember extraction Hyperspectral Material count estimation
Fully unsupervised hyperspectral image analysis / تحليل مكتمل بغير إشراف لصور الطيف الفائق Ahmed Mohamed Ahmed Saied Elsheikh ; Supervised Mohamed H. Farouk - Cairo : Ahmed Mohamed Ahmed Saied Elsheikh , 2014 - 113 P. : facsimiles ; 30cm
Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Mathematics and Physics
Spectroscopy is the study of light as a function of wavelength that has been emitted, reflected or scattered from a solid, liquid, or gas. Each material has its own spectral signature, and hence can be identified using spectral analysis. Hyperspectral imaging (HSI) - also called Imaging spectroscopy- sensors observe hundreds or thousands of contiguous spectral bands as well as spatial locality. A hyperspectral image cube (two spatial dimensions and the third is the wavelength) contains a large amount of information about the imaged scenario. Thus the automated analysis of such image cubes is an important asset. Spatial analysis in HSI is rather difficult due to the fact that HSI taken by a satellite or an airborne camera has low ground sampling distance (GSD). This means that many targets of interest can be located within one pixel. Another related problem is the availability of materials in nature as mixtures. As a result, spectral analysis is of great interest specially sub-pixel detection algorithms and spectral unmixing
Endmember extraction Hyperspectral Material count estimation