Assessment of effects of lossy compression of hyperspectral image data

Jonathan K. Su; Su May Hsu; Seth Orloff

doi:10.1117/12.538237

12 August 2004 Assessment of effects of lossy compression of hyperspectral image data

Jonathan K. Su, Su May Hsu, Seth Orloff

Proceedings Volume 5425, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X; (2004) https://doi.org/10.1117/12.538237
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

Hyperspectral imaging (HSI) sensors provide imagery with hundreds of spectral bands, typically covering VNIR and/or SWIR wavelengths. This high spectral resolution aids applications such as terrain classification and material identification, but it can also produce imagery that occupies well over 100 MB, which creates problems for storage and transmission. This paper investigates the effects of lossy compression on a representative HSI cube, with background classification serving as an example application. The compression scheme first performs principal components analysis spectrally, then discards many of the lower-importance principal-component (PC) images, and then applies JPEG2000 spatial compression to each of the individual retained PC images. The assessment of compression effects considers both general-purpose distortion measures, such as root mean square difference, and statistical tests for deciding whether compression causes significant degradations in classification. Experimental results demonstrate the effectiveness of proper PC-image rate allocation, which enabled compression at ratios of 100-340 without producing significant classification differences. Results also indicate that distortion might serve as a predictor of compression-induced changes in application performance.

Citation Download Citation

Jonathan K. Su, Su May Hsu, and Seth Orloff "Assessment of effects of lossy compression of hyperspectral image data", Proc. SPIE 5425, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X, (12 August 2004); https://doi.org/10.1117/12.538237

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KEYWORDS

Image compression

Distortion

JPEG2000

Statistical analysis

Hyperspectral imaging

Sensors

Library classification systems

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