Title :
Image fusion method and robustness test based on multiscale decomposition and spiking cortical model
Author :
Nianyi Wang ; Weilan Wang ; Yan Xu
Author_Institution :
Sch. of Math. & Comput. Sci. Inst., Northwest Univ. for Nat., Lanzhou, China
Abstract :
The main purpose of this paper is to find an efficient image fusion algorithm for multifocus images, based on the shift-invariance, multi-scale and multi-directional properties of nonsubsampled contourlet transform (NSCT) along with human visual characteristics of spiking cortical model (SCM). Firstly, maximum selection rule (MSR) is used to fuse low frequency coefficients of NSCT. Secondly, the time matrix of SCM is set as criteria to select coefficients of high frequency subband. The effectiveness of the proposed algorithm is achieved by the comparison with existing fusion methods. Objective tests and analysis conducted under different noised source image environments proved the robustness of the proposed fusion method.
Keywords :
image fusion; matrix algebra; neural nets; transforms; MSR; NSCT; SCM; frequency subband; human visual characteristics; image fusion algorithm; image fusion method; maximum selection rule; multifocus images; multiscale decomposition; nonsubsampled contourlet transform; robustness test; shift invariance; spiking cortical model; time matrix; Algorithm design and analysis; Computational modeling; Discrete wavelet transforms; Image fusion; Robustness; Visualization; image fusion; multimodal image fusion; nonsubsampled contourlet transform (NSCT); spiking cortical model (SCM);
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2013 3rd International Conference on
Conference_Location :
Xianning
Print_ISBN :
978-1-4799-2859-0
DOI :
10.1109/CECNet.2013.6703342
