''Reconfigurable Implementation of Wavelet Integer Lifting Transforms for Image Compression''
S. L. Bishop
J. L. Trahan
Proc. 3rd International Conference on ReConFigurable Computing and FPGAs (ReConFig'06), 2006, pp. 208-216
Modern digital image processing requires powerful data compression
algorithms to allow the data to be efficiently transferred from the
host to end users (and back again). A typical 512 x 512 grayscale
image of uncompressed data requires more than quarter of a million bytes.
Current image compression standards like JPEG2000 and the FBI WSQ
(wavelet scalar quantization) use wavelet transforms with quantization
to compress still images, which reconstruct with high accuracy.
This paper considers a number of popular 9/7 wavelet transform architectures.
High level software models are developed for these transforms to validate
their effectiveness. These software models are modified and evaluated as
reversible integer wavelet transforms. Further, using a virtual hardware
design targeted to reconfigurable FPGA technology these transforms are
implemented into a 2-D discrete wavelet transform (DWT) image processor
with DDR SDRAM operating at core speeds of 200+ MHz. Finally, our Matlab
and Maple models perform the validation of wavelet lifting transforms.
This work was supported in part by
the National Science Foundation under grant number CCR-0310916.