Lossless compression of hyperspectral images using C-DPCM-APL with reference bands selection

Keyan Wang; Huilin Liao; Yunsong Li; Shanshan Zhang; Xianyun Wu

doi:10.1117/12.2053479

28 May 2014 Lossless compression of hyperspectral images using C-DPCM-APL with reference bands selection

Keyan Wang, Huilin Liao, Yunsong Li, Shanshan Zhang, Xianyun Wu

Proceedings Volume 9124, Satellite Data Compression, Communications, and Processing X; 91240W (2014) https://doi.org/10.1117/12.2053479
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

The availability of hyperspectral images has increased in recent years, which is used in military and civilian applications, such as target recognition, surveillance, geological mapping and environmental monitoring. Because of its abundant data quantity and special importance, now it exists lossless compression methods of hyperspectral images mainly exploiting the strong spatial or spectral correlation. C-DPCM-APL is a method that achieves highest lossless compression ratio on the CCSDS hyperspectral images acquired in 2006 but consuming longest processing time among existing lossless compression methods to determine the optimal prediction length for each band. C-DPCM-APL gets best compression performance mainly via using optimal prediction length but ignoring the correlationship between reference bands and the current band which is a crucial factor that influences the precision of prediction. Considering this, we propose a method that selects reference bands according to the atmospheric absorption characteristic of hyperspectral images. Experiments on CCSDS 2006 images data set show that the proposed reduces the computation complexity heavily without decaying its lossless compression performance when compared to C-DPCM-APL.

Citation Download Citation

Keyan Wang, Huilin Liao, Yunsong Li, Shanshan Zhang, and Xianyun Wu "Lossless compression of hyperspectral images using C-DPCM-APL with reference bands selection", Proc. SPIE 9124, Satellite Data Compression, Communications, and Processing X, 91240W (28 May 2014); https://doi.org/10.1117/12.2053479

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