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Signal Processing Magazine, IEEE

Issue 1 • Date Jan 1995

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  • Practical transform coding of multispectral imagery

    Publication Year: 1995 , Page(s): 32 - 43
    Cited by:  Papers (43)  |  Patents (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1292 KB)  

    We present an implementable three dimensional terrain adaptive transform based bandwidth compression technique for multispectral imagery. The algorithm exploits the inherent spectral and spatial correlations in the data. The compression technique is based on Karhunen-Loeve transformation for spectral decorrelation followed by the standard JPEG algorithm for coding the resulting spectrally decorrelated eigen images. The algorithm is conveniently parameterized to accommodate reconstructed image fidelities ranging from near-lossless at about 5:1 CR to visually lossy beginning at about 30:1 CR. The novelty of this technique lies in its unique capability to adaptively vary the characteristics of the spectral correlation transformation as a function of the variation of the local terrain. The spectral and spatial modularity of the algorithm architecture allows the JPEG to be replaced by a alternate spatial coding procedure. The significant practical advantage of this proposed approach is that it is based on the standard and highly developed JPEG compression technology View full abstract»

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  • System considerations for multispectral image compression designs

    Publication Year: 1995 , Page(s): 19 - 31
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1116 KB)  

    Multispectral image (MSI) compression has evolved into a viable solution for band limited communications problems in current and future remote sensing systems. MSI compression technology continues to mature as research identifies the interaction of compression distortion and typical multispectral exploitation tasks. Understanding of both compression artifacts and exploitation techniques must proceed in parallel because sensitivity to errors (distortion) must be addressed for a much larger usage base. This article provides an introduction to the experience gained from the Advanced Land Remote Sensing System (ALRSS) compression development, and an insight into the challenges of MSI and space-based compression algorithm design. The ALRSS studies provide an initial look at the challenges of designing and evaluating MSI compression systems. The results of these studies have shown that compression rates between 2.2 and 1.3 bpp are viable and feasible for space-based applications today. MSI systems can be designed to include compression without changing the significance of the final image product View full abstract»

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IEEE Signal Processing Magazine publishes tutorial-style articles on signal processing research and applications, as well as columns and forums on issues of interest.

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

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