The Transform and Data Compression Handbook
The Transform and Data Compression Handbook
ISMW '07 Proceedings of the Ninth IEEE International Symposium on Multimedia Workshops
Optimal quality adaptation for scalable encoded video
IEEE Journal on Selected Areas in Communications
Highly scalable video compression with scalable motion coding
IEEE Transactions on Image Processing
A Fully Scalable Motion Model for Scalable Video Coding
IEEE Transactions on Image Processing
Source model for transform video coder and its application. I. Fundamental theory
IEEE Transactions on Circuits and Systems for Video Technology
Overview of the H.264/AVC video coding standard
IEEE Transactions on Circuits and Systems for Video Technology
Optimized Rate-Distortion Extraction With Quality Layers in the Scalable Extension of H.264/AVC
IEEE Transactions on Circuits and Systems for Video Technology
Overview of the Scalable Video Coding Extension of the H.264/AVC Standard
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Arbitrarily shaped virtual-object based video compression
Multimedia Tools and Applications
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Motion scalability is designed to improve the coding efficiency of a scalable video coding framework, especially in the medium to low range of decoding bit rates and spatial resolutions. In order to fully benefit from the superiority of motion scalability, a rate-distortion optimized bitstream extractor, which determines The optimal motion quality layer for any specific decoding scenario, IS required. In this paper, the determination process first starts off with a brute force searching algorithm. Although guaranteed by the optimal performance within the search domain, it suffers from high computational complexities. Two properties, i.e., the monotonically nondecreasing property and the unimodal property, are then derived to accurately describe the rate-distortion behavior of motion scalability. Based on these two properties, modified searching algorithms are proposed to reduce the complexity (up to five times faster) and to achieve the global optimality, even for those decoding scenarios outside the search domain.