Fast Stereo Video Coding Based on C-Means Fuzzy Hopfield Neural Network and AVS

Heng Zhi Cui; Chong Wang

doi:10.4028/www.scientific.net/AMM.344.230

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Research on Parameter Selection of Support Vector Regression
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Fast Stereo Video Coding Based on C-Means Fuzzy Hopfield Neural Network and AVS
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An Improvement Measure to AC-BM Pattern Matching Algorithm in Intrusion Defense System
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A Fast Interpolation Algorithm Based on the Fractal in the Digital Speckle Sub-Pixel Displacement Measurement
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Research on Behavioral Decision Method of Simulation Entity Based on Cognitive Model
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A Video Conferencing System for Collaborative Engineering Design
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 344Fast Stereo Video Coding Based on C-Means Fuzzy...

Fast Stereo Video Coding Based on C-Means Fuzzy Hopfield Neural Network and AVS

Abstract:

A fast stereo video coding method based-on C-Means Fuzzy Hopfield neural network and AVS (Audio and Video coding Standard) is presented in this paper. In the system, an AVS encoder encodes the left-view sequence. For the right-view sequence, combined predictions from the temporal or disparity domains are exploited, with a hierarchical two-stage neural classifier for fast mode decision. Experiment results show that our method can achieve up to 30% of time savings with nearly ignored quality degradation and only 7% of bit-rate increase.