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Adaptive multipattern Fast Block-Matching Algorithm Based on Motion Classification Techniques

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2008年第10期18卷 1369-1382页

作者： Gonzalez-Diaz, Ivan Diaz-de-Maria, Fernando Univ Carlos III Madrid Dept Signal Theory & Commun Madrid 28911 Spain

In most video coding standards, motion estimation becomes the most time-consuming subsystem. Consequently, in the last few years, a great deal of effort has been devoted to the research of novel algorithms capable of saving computations with minimal effects on the coding quality. Adaptive algorithms and particularly multipattern solutions, have evolved as the most robust general-purpose solutions owing to two main reasons: 1) real video sequences usually exhibit a wide-range of motion content, front uniform to random, and 2) a vast amount of coding applications have appeared demanding different degrees of coding quality. In this study. we propose an adaptive algorithm, called motion classification-based search (MCS), which makes use of an especially tailored classifier that detects some motion cues and chooses the search pattern that best fits them. The MCS has been experimentally assessed for a comprehensive set of selected video sequences and qualities. Our experimental results show that MCS notably reduces the computational cost up to 55 % and 84 % in search points, with respect to two state-of-the-art methods, while maintaining the quality.

关键词： Binary linear classifier block-matching motion classification motion estimation multipattern algorithms

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