Bio-inspired Neural Networks for Block based Motion Estimation

被引：0

作者：

Yuan, Youwei ^{[1
]}

Xu, Weilei ^{[1
]}

Yuan, Xudong ^{[2
]}

Yan, Lamei ^{[1
]}

Deris, M. Mat ^{[3
]}

机构：

[1] Hangzhou Dianzi Univ, Sch Comp Sci & Technol, Hangzhou 310018, Zhejiang, Peoples R China

[2] Zhejiang Univ, Dept Phys, Hangzhou 310007, Zhejiang, Peoples R China

[3] Univ Tun Hussein Onn Malaysia, Fac Comp Sci & Informat Technol, Johor Baharu 86400, Malaysia

来源：

JOURNAL OF ALGORITHMS & COMPUTATIONAL TECHNOLOGY | 2014年 / 8卷 / 04期

关键词：

Bio-inspired neural networks (BINN); Motion Estimation (ME); Peak signal-to-noise ratio (PSNR);

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In the multi-view video coding, both temporal and interview redundancies can be exploited by using standard block-based motion estimation technique. This paper describes a novel Bio-inspired neural networks model to enhance regions and extract contours of image for block-based motion estimation. We implements the optimized algorithm in the reference model of H. 264 compiled by VC6.0, and chooses six typical video sequences for simulation comparison. Experiments performed show the good visual results which can reduces the computational complexity in a certain degree and enhances encoding efficiency with few changes in the reconstructed image quality and bit rate.

引用

页码：471 / 482

页数：12

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