Precision vs. error in JPEG compression

By mapping computations directly onto hardware, reconfigurable machines promise a tremendous speed-up over traditional computers. However, executing floating-point operations directly in hardware is a waste of resources. Variable precision fixed-point arithmetic operations can save gates and reduce clock cycle times. This paper investigates the relation between precision and error for image compression/decompression. More precisely, this paper investigates the relationship between error and bit-precision for the Discrete Cosine Transform (DCT) and JPEG. The present work is part of the Cameron project at the Computer Science Department of Colorado State University. This project is roughly divided in three areas: an C-like parallel language called SA-C that is targeted for image processing on reconfigurable computers, an implementation of the VSIP library for image processing in SA-C, and an optimizing compiler for SA-C that targets FPGAs.