Stochastic determination of optimal wavelet compression strategies
Donald E. Waagen, Jeffrey D. Argast, John R. McDonnell · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994
Wavelet theory provides an attractive approach to signal and image compression. This work investigates a new wavelet transform coefficient selection approach for efficient image compression. For a desired image compression ratio (50:1), wavelet scale thresholds are derived via a multiagent stochastic optimization process. Previous work has demonstrated an interscale relationship between the stochastically optimized wavelet coefficient thresholds. Based on the experimental results, a deterministic wavelet coefficient selection criteria is hypothesized and the constants of the equation are statistically derived. Experimental results of the stochastic optimization and deterministic approaches are compared and contrasted with results from previously published wavelet coefficient threshold strategies.