Visible and infrared image fusion technique using advance fuzzy set theory

Abstract

Image fusion is the process of combining two or more images acquired from different image sensors into a single image which is advantageous for advance image processing assignments. In this work we present a new fusion method using fuzzy sets (FSs) that combine two or more images by using maximum, minimum operations in fuzzy images. In the processing stage, images are transformed into fuzzy images (FIs) in fuzzy plane. Fuzziness is applied to find the optimal value of the parameters of the fuzzy membership grades. The resulting FIs are fragmented into different fuzzy images depending on the range of dynamic intensity level. The partitioned fuzzy images are combined to find the optimal membership grade from partitioned fuzzy images and finally, fused image is obtained by defuzzification method. The experimental analysis shows that proposed method resolves the spectral distortion problems while preserving the spatial information and establishes that the proposed technique is outperforming all other state-of-the-art techniques in image fusion.

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Cite this paper

@article{Biswas2015VisibleAI, title={Visible and infrared image fusion technique using advance fuzzy set theory}, author={Biswajit Biswas and Biplab K. Sen}, journal={2015 IEEE International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)}, year={2015}, pages={96-101} }