Share Email Print
cover

Proceedings Paper

Residual coding with a JPEG2000 framework for controlling L-infinity error applied to ultraspectral sounder data
Author(s): Aldo Lucero; Sergio D. Cabrera; Edward Vidal
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

This paper presents a follow-up to last year's SPIE meeting where we presented a residual encoding method to control maximum absolute error (MAE) based on JPEG2000 Part 2 standard and which was applied to hyperspectral data. In this paper, we evaluate an improved version of the approach on the ultraspectral sounder satellite data made available by NOAA. The data set used consists of a subset of 1,501 bands out of the 2,378 total and where each band is an image of size 90 by 135 pixels. Each pixel or data value is a digital count integer that requires 12 - 14 bits to represent. We present compression performance using a transform in the band (z- or cross-component) direction. We use either the Karhunen-Loeve transform or the discrete wavelet transform with a non-uniform bit-rate allocation to take advantage of the energy compaction. One of the main features of this compression scheme is that residuals (original minus the decompressed values) are also coded in order to control the MAE; therefore, lossless compression can also be accomplished by using a desired MAE of 0.5. In all cases, the quantized residuals are losslessly encoded using the embedded block coding with optimized truncation (EBCOT) bit-plane encoding method that is part of JPEG2000 Part 1. Finally, our recent algorithm for automatically choosing the best (smallest total) combination of the two contributing bit rates is also extended to the 3-dimensional case. The two rates are: (1) the Open Loop rate for the lossy compression using JPEG2000 Part 2 by itself and (2) the EBCOT rate that results from the coding of the quantized residuals. The basis for the approach is the modeling of the residuals using generalized Gaussian random variables. Results for lossless and near-lossless compression will be presented using both an exhaustive search and the automatic search method for finding the minimum overall bit rate.

Paper Details

Date Published: 1 September 2006
PDF: 12 pages
Proc. SPIE 6300, Satellite Data Compression, Communications, and Archiving II, 630005 (1 September 2006); doi: 10.1117/12.682052
Show Author Affiliations
Aldo Lucero, The Univ. of Texas at El Paso (United States)
Sergio D. Cabrera, The Univ. of Texas at El Paso (United States)
Edward Vidal, Army Research Lab. (United States)


Published in SPIE Proceedings Vol. 6300:
Satellite Data Compression, Communications, and Archiving II
Roger W. Heymann; Charles C. Wang; Timothy J. Schmit, Editor(s)

© SPIE. Terms of Use
Back to Top