In this paper, a restricted instance of the LPP is analyzed, namely, the effect of reduced precision on image compression transforms. Particular emphasis is placed upon the compounding of representational error in the compression process as computation passes through various stages of a given algorithm. Analysis emphasizes effects of noise and computational error on common compression transforms such as visual pattern image coding, vector quantization, and a recently-developed algorithm called.
One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. This manuscript is an author version and may be cited as: Schmalz, M. S., Ritter, G. X., & Caimi, F. M. (1998), Limits on computational precision of image compression transformations. In M. S. Schmalz (Ed.), Mathematicsof data/image coding, compression, and encryption: July 21 - 22, 1998, San Diego, California. Sponsored and published by SPIE, the International Society for Optical Engineering. Proceedings of SPIE, 3456 (pp. 153-164). Bellingham, WA, USA. doi:10.1117/12.330366
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