Image Fusion Using Type-2 Fuzzy Systems

Image Fusion is a process of combining images from different sensors in order to get a single image having relevant information from all the sensors. Fuzzy logic based image fusion is introduced in order to incorporate uncertainty to the fusion logic since pixel calculation of the input image is not that certain and crisp. Recently studies are going on in Type-2 Fuzzy sets which can handle higher levels of uncertainties. Image Fusion algorithms using different types of Type-2 FLS s are developed and tested. It was observed that type-2 FLSs gives better values of Fusion quality performance metrics than Type-1 FLS. Among Type-2 FLSs, Type-2 Sugeno outperformed Mamdani. In Type-2 Mamdani FLSs, Type-2 Non-singleton type-2 Mamdani FLS was showing good results than the other two.

[1]  T. Meitzler,et al.  Iterative image fusion technique using fuzzy and neuro fuzzy logic and applications , 2005, NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society.

[2]  K Kashyap Sudesh.  Fusion of Long Wave Infra Red and Electro Optical ImagesUsing Fuzzy Logic Type 1 and Type 2 , 2013 .

[3]  Müzeyyen Bulut Özek,et al.  A software tool: Type‐2 fuzzy logic toolbox , 2008, Comput. Appl. Eng. Educ..

[4]  Harpreet Singh,et al.  Image fusion using fuzzy logic and applications , 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

[5]  Vps Naidu.  Discrete Cosine Transform based Image Fusion Techniques , 2012 .

[6]  Ling Yang,et al.  An Adaptive Image Fusion Method Based on Local Statistical Feature of Wavelet Coefficients , 2009, 2009 International Symposium on Computer Network and Multimedia Technology.

[7]  Somkait Udomhunsakul,et al.  Multi-focus Image Fusion Based on Stationary Wavelet Transform and Extended Spatial Frequency Measurement , 2009, 2009 International Conference on Electronic Computer Technology.

[8]  J. R. Raol,et al.  Pixel-level Image Fusion using Wavelets and Principal Component Analysis , 2008 .

[9]  Vps Naidu,et al.  Pixel Level Image Fusion using FuzzyletFusion Algorithm , 2013 .

[10]  Dongrui Wu,et al.  On the Fundamental Differences Between Interval Type-2 and Type-1 Fuzzy Logic Controllers , 2012, IEEE Transactions on Fuzzy Systems.

[11]  Jerry M. Mendel,et al.  Interval type-2 fuzzy logic systems , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[12]  Hani Hagras,et al.  Adaptive Non-singleton Type-2 Fuzzy Logic Systems: A Way Forward for Handling Numerical Uncertainties in Real World Applications , 2011, Int. J. Comput. Commun. Control.