Optimizing JPEG quantization matrices for different applications

JPEG has already found wide acceptance for still frame image compression. The quantization matrices (QMs) play a critical role in the performance of the JPEG algorithm but there has been a lack of effective QM design tools. As a result, sub-optimal QMs have commonly been used and JPEG has been judged to be inappropriate for some applications. It is our contention that JPEG is even more widely applicable than `common knowledge' would admit. This paper describes a low-cost design tool that has been developed and is currently being successfully applied to design QMs for various sensors including IR, SAR, medical, scanned maps, and fingerprints.