31 August 2009 Impact of JPEG2000 compression on spatial-spectral endmember extraction from hyperspectral data
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Hyperspectral image compression has received considerable interest in recent years. However, an important issue that has not been investigated in the past is the impact of lossy compression on spectral mixture analysis applications, which characterize mixed pixels in terms of a suitable combination of spectrally pure spectral substances (called endmembers) weighted by their estimated fractional abundances. In this paper, we specifically investigate the impact of JPEG2000 compression of hyperspectral images on the quality of the endmembers extracted by algorithms that incorporate both the spectral and the spatial information (useful for incorporating contextual information in the spectral endmember search). The two considered algorithms are the automatic morphological endmember extraction (AMEE) and the spatial spectral endmember extraction (SSEE) techniques. Experimental results are conducted using a well-known data set collected by AVIRIS over the Cuprite mining district in Nevada and with detailed ground-truth information available from U. S. Geological Survey. Our experiments reveal some interesting findings that may be useful to specialists applying spatial-spectral endmember extraction algorithms to compressed hyperspectral imagery.
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Gabriel Martín, Gabriel Martín, V. G. Ruiz, V. G. Ruiz, Antonio Plaza, Antonio Plaza, Juan P. Ortiz, Juan P. Ortiz, Inmaculada García, Inmaculada García, } "Impact of JPEG2000 compression on spatial-spectral endmember extraction from hyperspectral data", Proc. SPIE 7455, Satellite Data Compression, Communication, and Processing V, 74550A (31 August 2009); doi: 10.1117/12.826318; https://doi.org/10.1117/12.826318

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