Distortion estimation for optimized delivery of JPEG2000 compressed video with motion

Abstract

A JPEG2000 compressed video sequence can provide better support for scalability, flexibility, and accessibility at a wider range of bit-rates than the current motion-compensated predictive video coding standards; however, it requires considerably more bandwidth to stream. The authors have recently proposed a novel approach that reduces the required bandwidth; this approach uses motion compensation and conditional replenishment of JPEG2000 code-blocks, aided by server-optimized selection of these code-blocks. The proposed approach can serve a diverse range of client requirements and can adapt immediately to interactive changes in client interests, such as forward or backward playback and zooming into individual frames. This work extends the previous work by approximating the distortion associated with the decisions made by the server without the need to recreate the actual video sequence at the server. The proposed distortion estimation algorithm is general and can be applied to various frames arrangements. Here, we choose to employ it in a hierarchical arrangement of frames, similar to the hierarchical B-frames of the SVC scalable video coding extension of the H.264/AVC standard. We employ a Lagrangian-style rate-distortion optimization procedure to the server transmission problem and compare the performance of both distortion estimation and exact distortion calculation cases against streaming individual frames and SVC. Results obtained suggest that the distortion estimation algorithm considerably reduces the amount of calculation needed by the server without enormously degrading the performance compared to the exact distortion calculation case. This work introduces the concepts, formulates the estimation and optimization problems, proposes a solution, and compares the performance to alternate strategies.