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Signal Processing Magazine, IEEE

Issue 1 • Date Jan. 2002

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Displaying Results 1 - 6 of 6
  • President's Message

    Publication Year: 2002 , Page(s): 2 - 5
    Request Permissions | PDF file iconPDF (159 KB) |  | HTML iconHTML  
    Freely Available from IEEE
  • Signal processing for hyperspectral image exploitation

    Publication Year: 2002 , Page(s): 12 - 16
    Cited by:  Papers (67)  |  Patents (4)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (7793 KB)  

    Electro-optical remote sensing involves the acquisition of information about an object or scene without coming into physical contact with it. This is achieved by exploiting the fact that the materials comprising the various objects in a scene reflect, absorb, and emit electromagnetic radiation in ways characteristic of their molecular composition and shape. If the radiation arriving at the sensor ... View full abstract»

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  • Hyperspectral image data analysis

    Publication Year: 2002 , Page(s): 17 - 28
    Cited by:  Papers (210)  |  Patents (6)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (4080 KB) |  | HTML iconHTML  

    The fundamental basis for space-based remote sensing is that information is potentially available from the electromagnetic energy field arising from the Earth's surface and, in particular, from the spatial, spectral, and temporal variations in that field. Rather than focusing on the spatial variations, which imagery perhaps best conveys, why not move on to look at how the spectral variations might... View full abstract»

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  • Detection algorithms for hyperspectral imaging applications

    Publication Year: 2002 , Page(s): 29 - 43
    Cited by:  Papers (220)  |  Patents (12)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (3766 KB) |  | HTML iconHTML  

    We introduce key concepts and issues including the effects of atmospheric propagation upon the data, spectral variability, mixed pixels, and the distinction between classification and detection algorithms. Detection algorithms for full pixel targets are developed using the likelihood ratio approach. Subpixel target detection, which is more challenging due to background interference, is pursued usi... View full abstract»

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  • Anomaly detection from hyperspectral imagery

    Publication Year: 2002 , Page(s): 58 - 69
    Cited by:  Papers (151)  |  Patents (16)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1226 KB) |  | HTML iconHTML  

    We develop anomaly detectors, i.e., detectors that do not presuppose a signature model of one or more dimensions, for three clutter models: the local normal model, the global normal mixture model, and the global linear mixture model. The local normal model treats the neighborhood of a pixel as having a normal probability distribution. The normal mixture model considers the observation from each pi... View full abstract»

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  • Spectral unmixing

    Publication Year: 2002 , Page(s): 44 - 57
    Cited by:  Papers (539)  |  Patents (25)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (7193 KB) |  | HTML iconHTML  

    Spectral unmixing using hyperspectral data represents a significant step in the evolution of remote decompositional analysis that began with multispectral sensing. It is a consequence of collecting data in greater and greater quantities and the desire to extract more detailed information about the material composition of surfaces. Linear mixing is the key assumption that has permitted well-known a... View full abstract»

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Aims & Scope

IEEE Signal Processing Magazine publishes tutorial-style articles on signal processing research and applications, as well as columns and forums on issues of interest. Its coverage ranges from fundamental principles to practical implementation, reflecting the multidimensional facets of interests and concerns of the community. Its mission is to bring up-to-date, emerging and active technical developments, issues, and events to the research, educational, and professional communities. It is also the main Society communication platform addressing important issues concerning all members.

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Meet Our Editors

Editor-in-Chief
Min Wu
University of Maryland, College Park
United States 

http://www/ece.umd.edu/~minwu/