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
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;
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
DOI :
10.1109/ICADIWT.2009.5273861
