Image fusion algorithm based on energy of Laplacian and PCNN

Meili Li, Hongmei Wang, Yanjun Li, Ke Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Owing to the global coupling and pulse synchronization characteristic of pulse coupled neural networks (PCNN), it has been proved to be suitable for image processing and successfully employed in image fusion. However, in almost all the literatures of image processing about PCNN, linking strength of each neuron is assigned the same value which is chosen by experiments. This is not consistent with the human vision system in which the responses to the region with notable features are stronger than that to the region with nonnotable features. It is more reasonable that notable features, rather than the same value, are employed to linking strength of each neuron. As notable feature, energy of Laplacian (EOL) is used to obtain the value of linking strength in PCNN in this paper. Experimental results demonstrate that the proposed algorithm outperforms Laplacian-based, wavelet-based, PCNN -based fusion algorithms.

Original languageEnglish
Title of host publicationInternational Conference on Space Information Technology 2009
DOIs
StatePublished - 2010
EventInternational Conference on Space Information Technology 2009 - Beijing, China
Duration: 26 Nov 200927 Nov 2009

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7651
ISSN (Print)0277-786X

Conference

ConferenceInternational Conference on Space Information Technology 2009
Country/TerritoryChina
CityBeijing
Period26/11/0927/11/09

Fingerprint

Dive into the research topics of 'Image fusion algorithm based on energy of Laplacian and PCNN'. Together they form a unique fingerprint.

Cite this