Fast Inter-Layer Motion Estimation Algorithm on Spatial Scalability in H.264/AVC Scalable Extension

Abstract

With the improvements of video coding technology, network infrastructures, storage capacity, and CPU computing capability, the applications of multimedia systems become wider and more popular. Therefore, how to efficiently provide video sequences to users under different constraints is very important, and scalable video coding is one of the best solutions to this problem.

H.264 scalable extension (SVC) that is constructed based on H.264/AVC is the most recent scalable video coding standard. SVC utilizes the inter-layer prediction to substantially improve the coding efficiency comparing with the prior scalable video coding standards. Nevertheless, this technique results in extremely large computation complexity which obstructs it from practical use. Especially on spatial scalability, the complexity of the enhancement layer motion estimation occupies above 90% of the total complexity. The main objective of this work is to reduce the computation complexity while maintaining both the video quality and the bit-rate.

This thesis proposes a fast inter-layer motion estimation algorithm on temporal and spatial scalabilities for SVC. We utilize the relation between two motion vector predictors from the base layer as well as the enhancement layer respectively and the correlation between all the modes to reduce the number of search times. The simulation results show that the proposed algorithm can save the computation complexity up to 67.4% compared to JSVM9.12 with less than 0.0476dB video quality degradation.