Details

Autor(en) / Beteiligte

• Qian Du
• Fowler, J.E.

Titel

Hyperspectral Image Compression Using JPEG2000 and Principal Component Analysis

Ist Teil von

• IEEE geoscience and remote sensing letters, 2007-04, Vol.4 (2), p.201-205

Ort / Verlag

Piscataway: IEEE

Erscheinungsjahr

2007

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• Principal component analysis (PCA) is deployed in JPEG2000 to provide spectral decorrelation as well as spectral dimensionality reduction. The proposed scheme is evaluated in terms of rate-distortion performance as well as in terms of information preservation in an anomaly-detection task. Additionally, the proposed scheme is compared to the common approach of JPEG2000 coupled with a wavelet transform for spectral decorrelation. Experimental results reveal that, not only does the proposed PCA-based coder yield rate-distortion and information-preservation performance superior to that of the wavelet-based coder, the best PCA performance occurs when a reduced number of PCs are retained and coded. A linear model to estimate the optimal number of PCs to use in such dimensionality reduction is proposed