標題: CNN-based local motion estimation chip for image stabilization processing
作者: Lin, Chin-Teng
Chen, Shi-An
Cheng, Ying-Chang
Chung, Jen-Feng
電控工程研究所
Institute of Electrical and Control Engineering
公開日期: 2006
摘要: 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. The complete design has integrated into the total area of 8.1mm(2) by using TSMC 0.35 mu m mixed-signal process.
URI: http://hdl.handle.net/11536/17266
ISBN: 978-0-7803-9389-9
ISSN: 0271-4302
期刊: 2006 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1-11, PROCEEDINGS
起始頁: 2645
結束頁: 2648
Appears in Collections:Conferences Paper