Vector quantization with reversible variable-length coding for ultra-spectral sounder data compression: an application to future NOAA weather satellite data rebroadcast

2007 ◽  
Author(s):  
Bormin Huang ◽  
Shih-Chieh Wei
Keyword(s):  
Data Compression ◽  
Vector Quantization ◽  
Satellite Data ◽  
Variable Length ◽  
Variable Length Coding

A Test Data Compression Scheme Based on Mixed Fixed and Variable Length Coding

2009 ◽  
Vol 31 (10) ◽  
pp. 1826-1834 ◽  
Author(s):  
Wen-Fa ZHAN ◽  
Hua-Guo LIANG ◽  
Feng SHI ◽  
Zheng-Feng HUANG
Keyword(s):  
Data Compression ◽  
Test Data ◽  
Variable Length ◽  
Test Data Compression ◽  
Compression Scheme ◽  
Variable Length Coding

scholarly journals Optimal Compression of High Spectral Resolution Satellite Data via Adaptive Vector Quantization with Linear Prediction

2008 ◽  
Vol 25 (6) ◽  
pp. 1041-1047 ◽  
Author(s):  
Bormin Huang ◽  
Alok Ahuja ◽  
Hung-Lung Huang
Keyword(s):  
Data Compression ◽  
Vector Quantization ◽  
Satellite Data ◽  
Spectral Resolution ◽  
Image Coding ◽  
Linear Prediction ◽  
Lossless Compression ◽  
High Spectral Resolution ◽  
Adaptive Vector Quantization ◽  
Space Data

Abstract Contemporary and future high spectral resolution sounders represent a significant technical advancement for environmental and meteorological prediction and monitoring. Given their large volume of spectral observations, the use of robust data compression techniques will be beneficial to data transmission and storage. In this paper, a novel adaptive vector quantization (VQ)-based linear prediction (AVQLP) method for lossless compression of high spectral resolution sounder data is proposed. The AVQLP method optimally adjusts the quantization codebook sizes to yield the maximum compression on prediction residuals and side information. The method outperforms the state-of-the-art compression methods [Joint Photographic Experts Group (JPEG)-LS, JPEG2000 Parts 1 and 2, Consultative Committee for Space Data Systems (CCSDS) Image Data Compression (IDC) 5/3, Context-Based Adaptive Lossless Image Coding (CALIC), and 3D Set Partitioning in Hierarchical Trees (SPIHT)] and achieves a new high in lossless compression for the standard test set of 10 NASA Atmospheric Infrared Sounder (AIRS) granules. It also compares favorably in terms of computational efficiency and compression gain to recently reported adaptive clustering methods for lossless compression of high spectral resolution data. Given its superior compression performance, the AVQLP method is well suited to ground operation of high spectral resolution satellite data compression for rebroadcast and archiving purposes.

Ultraspectral sounder data compression using error-detecting reversible variable-length coding

2005 ◽  
Author(s):  
Bormin Huang ◽  
Alok Ahuja ◽  
Hung-Lung Huang ◽  
Timothy J. Schmit ◽  
Roger W. Heymann
Keyword(s):  
Data Compression ◽  
Variable Length ◽  
Error Detecting ◽  
Variable Length Coding

Fusion of dynamic predictive block adaptive quantization and vector quantization for staggered SAR data compression

2020 ◽  
Vol 12 (2) ◽  
pp. 206-215
Author(s):  
Hang Zou ◽  
Fengjun Zhao ◽  
Xiaoxue Jia ◽  
Heng Zhang ◽  
Wei Wang
Keyword(s):  
Data Compression ◽  
Vector Quantization ◽  
Adaptive Quantization ◽  
Sar Data
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