z-logo
open-access-imgOpen Access
Evaluation of onboard hyperspectral-image compression techniques for a parallel push-broom sensor
Author(s) -
S Briles
Publication year - 1996
Language(s) - English
Resource type - Reports
DOI - 10.2172/212527
Subject(s) - hyperspectral imaging , row , computer science , data compression , mean squared error , computer vision , full spectral imaging , artificial intelligence , wavelet , remote sensing , mathematics , geography , statistics , database
A single hyperspectral imaging sensor can produce frames with spatially-continuous rows of differing, but adjacent, spectral wavelength. If the frame sample-rate of the sensor is such that subsequent hyperspectral frames are spatially shifted by one row, then the sensor can be thought of as a parallel (in wavelength) push-broom sensor. An examination of data compression techniques for such a sensor is presented. The compression techniques are intended to be implemented onboard a space-based platform and to have implementation speeds that match the date rate of the sensor. Data partitions examined extend from individually operating on a single hyperspectral frame to operating on a data cube comprising the two spatial axes and the spectral axis. Compression algorithms investigated utilize JPEG-based image compression, wavelet-based compression and differential pulse code modulation. Algorithm performance is quantitatively presented in terms of root-mean-squared error and root-mean-squared correlation coefficient error. Implementation issues are considered in algorithm development

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here