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Nonsubsampled contourlet transform (NSCT) 能够提供灵活的多分辨率分解, 具有各向异性和图像方向性扩展特点. 与原始的Contourlet相比, 它是频移不变的, 能有效克服Contourlet变换中的伪吉布斯现象. 脉冲耦合神经网络(Pulse Coupled Neural Networks-PCNN)是一种具有视觉生理学基础的神经网络, 具有全局耦合和神经元同步脉冲发放特性, 已经被成功应用于图像处理和图像融合中. 本文将NSCT与PCNN结合起来, 充分利用二者的特性. 以NSCT变换域内系数的空间频率激励PCNN神经元, 选择点火次数大的系数作为融合图像的系数, 经NSCT反变换得到融合图像. 实验表明, 本文算法无论在视觉效果还是客观评价指标上, 都优于基于小波变换、基于Contourlet变换、基于PCNN和基于Contourlet-PCNN等融合算法.
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Image Processing Using Pulse-Coupled Neural Networks
T. Lindblad J.M. Kinser
Image Processing
Using Pulse-Coupled
Neural Networks
Second, Revised Edition
With 140 Figures
123
Professor Dr. Thomas Lindblad
Royal Institute of Technology, KTH-Physics, AlbaNova
S-10691 Stockholm, Sweden
E-mail: Lindblad@particle.kth.se
ProfessorDr.JasonM.Kinser
George Mason University
MSN 4E3, 10900 University Blvd., Manassas, VA 20110, USA, and
12230 Scones Hill Ct., Bristow VA, 20136, USA
E-mail: jkinser@gmu.edu
Library of Congress Control Number: 2005924953
ISBN-10 3-540-24218-X 2nd Edition, Springer Berlin Heidelberg New York
ISBN-13 978-3-540-24218-5 2nd Edition Springer Berlin Heidelberg New York
ISBN 3-540-76264-7 1st E dition, Springer Berlin Heidelberg New York
This work is subject to copyright. All rights are reserved, whether the whole or part of the material
is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broad-
casting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of
this publication or parts thereof is permitted only under the provisions of the German Copyright Law
of September 9, 1965, in its current version, and permission for use must always be obtained from
Springer. Violations are liable to prosecution under the German Copyri ght Law.
Springer is a part of Springer Science+Business Media.
springeronline.com
© Springer-Verlag Berlin Heidelberg 1998, 2005
Printed in The Netherlands
The use of general descr iptive names, registered names, trademarks, etc. in this publication does not
imply, even in the absence of a specific statement, that such names are exempt from the relevant pro-
tective laws and regulations and therefore free for general use.
Typesetting and prodcution: PTP-Berlin, Protago-T
E
X-Production GmbH, Berlin
Cover design: design & production GmbH, Heidelberg
Printed on acid-free paper SPIN 10965221 57/3141/YU 543210
Preface
It was stated in the preface to the first edition of this book that image pro-
cessing by electronic means has been a very active field for decades. This
is certainly still true and the goal has been, and still is, to have a machine
perform the same image functions which humans do quite easily. In reaching
this goal we have learnt about the human mechanisms and how to apply this
knowledge to image processing problems. Although there is still a long way to
go, we have learnt a lot during the last five or six years. This new information
and some ideas based upon it has been added to the second edition of our book
The present edition includes the theory and application of two cortical
models: the PCNN (pulse coupled neural network) and the ICM (intersecting
cortical model). These models are based upon biological models of the visual
cortex and it is prudent to review the algorithms that strongly influenced the
development of the PCNN and ICM. The outline of the book is otherwise
very much the same as in the first edition although several new application
examples have been added.
In Chap. 7 a few of these applications will be reviewed including original
ideas by co-workers and colleagues. Special thanks are due to Soonil D.D.V.
Rughooputh, the dean of the Faculty of Science at the University of Mauritius
Guisong, and Harry C.S. Rughooputh, the dean of the Faculty of Engineering
at the University of Mauritius.
We should also like to acknowledge that Guisong Wang, a doctoral can-
didate in the School of Computational Sciences at GMU, made a significant
contribution to Chap. 5.
We would also like to acknowledge the work of several diploma and Ph.D.
students at KTH, in particular Jenny Atmer, Nils Zetterlund and Ulf Ekblad.
Stockholm and Manassas, Thomas Lindblad
April 2005 Jason M. Kinser
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资源评论
- wuyihust2012-12-08谢谢分享,很有用
- qjs4122014-07-15论文不错,对自己很有用,谢谢
- j_iafeng2012-05-03论文不错,讲解很详细,算法可以实现
- doudingchenlei2014-04-27讲解的很好,跟我毕业设计的东西很挂钩,帮助很大
- coolbcb2017-09-25文不错,讲解很详细
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