標題: CNN-based local motion estimation for image stabilization processing and its implementation
作者: Chin-Teng Lin
Shi-An Chen
Ying-Chang Cheng
Chao-Ting Hong
電控工程研究所
Institute of Electrical and Control Engineering
公開日期: 2006
摘要: The objective of this paper is to investigate a novel design for local motion vectors (LMVs) of image sequences, which are often used in a digital image stabilization (IS) system. The IS technique removes unwanted shaking phenomenon in image sequences captured by hand-held camcorders. It includes two main parts such as motion estimation and compensation. Most of computation power occurs in the part of motion estimation. In order to reduce this complexity, an idea, which integrates an adaptive-threshold method and cellular neural networks (CNN) architecture, is designed to improve this problem. The design only implements the most important local motion estimation with the array size of 19x25 pixels. Experimental results with HSPICE simulation and CNNUM are shown that the proposed architecture fast searches the location of possible LVMs and has the capability of real-time operations.
URI: http://hdl.handle.net/11536/17224
http://dx.doi.org/10.1109/ICSMC.2006.384993
ISBN: 978-1-4244-0099-7
ISSN: 1062-922X
DOI: 10.1109/ICSMC.2006.384993
期刊: 2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS
起始頁: 1816
結束頁: 1819
Appears in Collections:Conferences Paper


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