Reduced Complexity Wavelet-Based Predictive Coding of Hyperspectral Images for FPGA Implementation

We present an algorithm for lossy compression of hyperspectral images for implementation on field programmable gate arrays (FPGA). To greatly reduce the bit rate required to code images, we use linear prediction between the bands to exploit the large amount of inter-band correlation. The prediction residual is compressed using the Set Partitioning in Hierarchical Trees algorithm. To reduce the complexity of the predictive encoder, we propose a bit plane-synchronized closed loop predictor that does not require full decompression of a previous band at the encoder. The new technique achieves similar compression ratios to that of standard closed loop predictive coding and has a simpler on-board implementation.

• Type: Conference
• Year: 2004
• Where: DCC
• Authors: Agnieszka C. Miguel, Amanda R. Askew, Alexander Chang, Scott Hauck, Richard E. Ladner, Eve A. Riskin
• Keywords: Closed Loop Predictor, Computer Graphics, DCC 2004, Loop Predictive Coding, Simpler On-board Implementation