Approximating Rate-Distortion Graphs of Individual Data: Experiments in Lossy Compression and Denoising

Classical rate-distortion theory requires knowledge of an elusive source distribution. Instead, we analyze rate-distortion properties of individual objects using the recently developed algorithmic rate-distortion theory. The latter is based on the noncomputable notion of Kolmogorov complexity. To apply the theory we approximate the Kolmogorov complexity by standard data compression techniques, and perform a number of experiments with lossy compression and denoising of objects from different domains. We also introduce a natural generalization to lossy compression with side information. To maintain full generality we need to address a difficult searching problem. While our solutions are therefore not time efficient, we do observe good denoising and compression performance.

• Type: Journal
• Year: 2006
• Where: CORR
• Authors: Steven de Rooij, Paul M. B. Vitányi
• Keywords: Classical Rate-distortion Theory, CORR 2006, Education, Kolmogorov Complexity, Rate-distortion Theory