Title :
Research on Spatial Frequency Motivated Gray Level Image Fusion Based on Improved PCNN
Author :
Nianyi Wang ; Yide Ma ; Weilan Wang
Author_Institution :
Sch. of Math. & Comput. Sci., Inst. Northwest Univ. for Nat., Lanzhou, China
Abstract :
SCM is an improved PCNN model compared to traditional PCNN model. It decreased computation complexity and needs less computing compared to PCNN. It accords with Weber-Fechner law. It also possesses the excellent features of both PCNN model and ICM model. A SCM based image fusion method is presented in this paper. Firstly, we set an important image function - spatial frequency (SF) as stimulus to activate SCM networks. And then we provided a new method to select pixels from original images and generate the fusion result image. For proving the effectiveness of our SCM-based method, we compared it with other five methods under four image fusion effect evaluation indices. The Comparison of different fusion results show effectiveness of our fusion approach. Robustness test experiments verify that our method can be used in noisy image processing field.
Keywords :
computational complexity; image colour analysis; image denoising; image fusion; neural nets; SCM; Weber-Fechner law; computation complexity; gray level image fusion; improved PCNN; noisy image processing; pulse coupled neural network; spatial frequency; spiking cortical model; Brain modeling; Computational modeling; Educational institutions; Image fusion; Robustness; Visualization; image fusion; pulse coupled neural network (PCNN); robustness test; spatial frequency;
Conference_Titel :
Information Science and Cloud Computing Companion (ISCC-C), 2013 International Conference on
Conference_Location :
Guangzhou
DOI :
10.1109/ISCC-C.2013.115