Paper
17 November 1995 Practical issues for transform coding of multispectral imagery
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Abstract
An overview of a robust and implementable compression algorithm previously developed for multispectral imagery is given. This three-dimensional terrain-adaptive transform-based algorithm involves a one dimensional Karhunen-Loeve (KLT) transform followed by two- dimensional discrete cosine transform. The images are spectrally decorrelated via the KLT to produce the eigen images. The resulting spectrally-decorrelated eigen images are then compressed using the JPEG algorithm. The key feature of this approach is that it incorporates the best methods available to fully exploit the spectral and spatial correlation in the data. The novelty of this technique lies in its unique capability to adaptively vary the characteristics of the spectral decorrelation transformation based upon variations in the local terrain. In addition several relevant practical issues are addressed. These issues include: (1) Handling the panchromatic sharpening band, (2) tradeoff between spectral and spatial fidelity, (3) different grouping of bands for spectral decorrelation, (4) impact of band misalignment on performance, (5) impact of dead and saturated pixels on performance, and (6) impact of preprocessing on performance.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John A. Saghri, Andrew G. Tescher, and John T. Reagan "Practical issues for transform coding of multispectral imagery", Proc. SPIE 2587, Geographic Information Systems, Photogrammetry, and Geological/Geophysical Remote Sensing, (17 November 1995); https://doi.org/10.1117/12.226812
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Cited by 1 scholarly publication.
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KEYWORDS
Image compression

Multispectral imaging

Algorithm development

Image processing

Quantization

Visualization

Visual compression

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