Visual relevance evaluation using Rate Distortion analysis in the Circular Harmonic Functions Domain

In this paper we develop a strategy for visual relevancy evaluation using Rate Distortion analysis in the Circular Harmonic Functions (CHF) Domain. In the CHF domain, the different visual characteristics of the transformed frames - edges, lines, forks, crosses, etc - are emphasized. Resorting to this domain we analyze a new approach to evaluate the distortion due to an event of video data loss accounting for the visual relevance of individual lost data. In a real video streaming session, distortion measurements taking into account the visual impact of error events can be stored along with pre-coded video sequence so as to drive the strategies for ad-hoc error protection. Numerical simulations show that the approach herein proposed to evaluate the visual impact of loss events in the decoded sequences captures the visual distortion much better than commonly adopted mean square error criteria between the decoded and the original sequence.