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Journal of Sensors
Volume 2016, Article ID 8359602, 12 pages
http://dx.doi.org/10.1155/2016/8359602
Research Article

Multifocus Color Image Fusion Based on NSST and PCNN

Information College, Yunnan University, Kunming 650091, China

Received 7 August 2015; Revised 29 October 2015; Accepted 5 November 2015

Academic Editor: Claudio Lugni

Copyright © 2016 Xin Jin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper proposed an effective multifocus color image fusion algorithm based on nonsubsampled shearlet transform (NSST) and pulse coupled neural networks (PCNN); the algorithm can be used in different color spaces. In this paper, we take HSV color space as an example, H component is clustered by adaptive simplified PCNN (S-PCNN), and then the H component is fused according to oscillation frequency graph (OFG) of S-PCNN; at the same time, S and V components are decomposed by NSST, and different fusion rules are utilized to fuse the obtained results. Finally, inverse HSV transform is performed to get the RGB color image. The experimental results indicate that the proposed color image fusion algorithm is more efficient than other common color image fusion algorithms.