Lossless Compression for Space Imagery in a Dynamically Reconfigurable Architecture

This paper presents a novel dynamically reconfigurable hardware architecture for lossless compression and its optimization for space imagery. The proposed system makes use of reconfiguration to support optimal modeling strategies adaptively for data with different dimensions. The advantage of the pr...

Full description

Saved in:
Bibliographic Details
Published inReconfigurable Computing: Architectures, Tools and Applications Vol. 4943; pp. 336 - 341
Main Authors Chen, Xiaolin, Canagarajah, C. Nishan, Vitulli, Raffaele, Nunez-Yanez, Jose L.
Format Book Chapter
LanguageEnglish
Published Germany Springer Berlin / Heidelberg 2008
Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
Compression Function
Lossless Compression
Lossless Image Compression
Multispectral Image
Probability Estimator
Online AccessGet full text

Cover

More Information
Summary:This paper presents a novel dynamically reconfigurable hardware architecture for lossless compression and its optimization for space imagery. The proposed system makes use of reconfiguration to support optimal modeling strategies adaptively for data with different dimensions. The advantage of the proposed system is the efficient combination of different compression functions. For image data, we propose a new multi-mode image model which can detect the local features of the image and use different modes to encode regions with different features. Experimental results show that our system improves compression ratios of space image while maintaining low complexity and high throughput.
ISBN:3540786090
9783540786092
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-540-78610-8_38