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.
|Translated title of the contribution||Lossless compression for space imagery in a dynamically reconfigurable architecture|
|Title of host publication||4th International Workshop on Reconfigurable Computing: Architectures, Tools and Applications (ARC 2008), London, UK|
|Pages||336 - 341|
|Number of pages||6|
|Publication status||Published - 26 Mar 2008|