DocumentCode
3539245
Title
Image fusion based on steerable pyramid and PCNN
Author
Deng, Haibo ; Ma, Yide
Author_Institution
Sch. of Inf. Sci. & Eng., Lanzhou Univ., Lanzhou, China
fYear
2009
fDate
4-6 Aug. 2009
Firstpage
569
Lastpage
573
Abstract
A new image fusion algorithm, based on steerable pyramid and Pulse Coupled Neural Network (PCNN), is proposed in this paper. First, original images are decomposed into several subbands of different levels and orientations by steerable pyramid. Then, low frequency subbands are fused by weighting and high frequency subbands are fused by PCNN. The fused image is obtained by inverse steerable pyramid transform. Results testify our approach in comparison with wavelets fusion in both subjective visual effect and objective evaluation criteria while using four different pairs of test images.
Keywords
image fusion; neural nets; wavelet transforms; frequency subbands; image fusion algorithm; inverse steerable pyramid transform; pulse coupled neural network; wavelet fusion; Discrete wavelet transforms; Filters; Frequency; Image converters; Image fusion; Image sensors; Intelligent sensors; Layout; Sensor fusion; Testing; Image Fusion; PCNN; Steerable Pyramid; Wavelets;
fLanguage
English
Publisher
ieee
Conference_Titel
Applications of Digital Information and Web Technologies, 2009. ICADIWT '09. Second International Conference on the
Conference_Location
London
Print_ISBN
978-1-4244-4456-4
Electronic_ISBN
978-1-4244-4457-1
Type
conf
DOI
10.1109/ICADIWT.2009.5273861
Filename
5273861
Link To Document