Content-Adaptive Motion Estimation Algorithm for Coarse-Grain SVC

• Published in: IEEE transactions on image processing Vol. 21; no. 5; pp. 2582 - 2591
• Main Authors: Shen, Liquan, Zhang, Zhaoyang
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.05.2012; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Coding; Complexity; Computation; Computational complexity; Correlation; Detection, estimation, filtering, equalization, prediction; Distortion; Encoders; Encoding; Exact sciences and technology; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image processing; Information, signal and communications theory; Interlayer correlation; Mathematical models; Motion; motion estimation (ME); Pattern Recognition, Automated - methods; Prediction algorithms; Reproducibility of Results; scalable video coding (SVC); Searching; Sensitivity and Specificity; Signal and communications theory; Signal processing; Signal, noise; spatial correlation; Static VAr compensators; Strontium; Studies; Subtraction Technique; Telecommunications and information theory; Vectors; Video Recording - methods; Video coding; Interfacial layer; Performance evaluation; Adaptive algorithm; Motion estimation; Scalability; Image processing; Coding circuit; Spatial correlation; scalable video coding (SVC); Rate distortion theory; motion estimation (ME); Adaptive estimation; Enhancement layer; Computational complexity; Adaptive method; Video signal processing; Enhancement mode; Signal processing; Content analysis; Interlayer correlation
• ISSN: 1057-7149; 1941-0042; 1941-0042
• DOI: 10.1109/TIP.2011.2177849

A joint model of scalable video coding (SVC) uses exhaustive mode and motion searches to select the best prediction mode and motion vector for each macroblock (MB) with high coding efficiency at the cost of computational complexity. If major characteristics of a coding MB such as the complexity of the prediction mode and the motion property can be identified and used in adjusting motion estimation (ME), one can design an algorithm that can adapt coding parameters to the video content. This way, unnecessary mode and motion searches can be avoided. In this paper, we propose a content-adaptive ME for SVC, including analyses of mode complexity and motion property to assist mode and motion searches. An experimental analysis is performed to study interlayer and spatial correlations in the coding information. Based on the correlations, the motion and mode characteristics of the current MB are identified and utilized to adjust each step of ME at the enhancement layer including mode decision, search-range selection, and prediction direction selection. Experimental results show that the proposed algorithm can significantly reduce the computational complexity of SVC while maintaining nearly the same rate distortion performance as the original encoder.