Quantitative analysis of fused infrared and visible images using spatial and transform domain techniques

Image fusion aims to integrate complementary information from multiple modalities into a single image with none distortion and loss of data. Image fusion is important in medical imaging, specifically for the purpose of detecting the tumor and identification of diseases. In this article, completely unique discrete wavelet transform (DWT) and intuitionistic fuzzy sets (IFSs) based fusion method (DWT-IFS) is proposed. For fusion, initially, all source images are fused using DWT with the average, maximum, and entropy fusion rules. Besides, on the fused image IFS is applied. In the IFS process images are converted into intuitionistic fuzzy images (IFIs) by selecting an optimum value for the parameter in membership, non-membership, and hesitation degree function using entropy. Then, the resulting IFIs are decomposed into the blocks, and the corresponding blocks of the images are fused using the intersection and union operations of IFS.

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An Efficient DWT and Intuitionistic Fuzzy Based Multimodality Medical Image Fusion

Soundrapandiyan

Karuppiah

Kumari

et al. 2017

Int J Imaging Syst Tech

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Quantitative analysis of fused infrared and visible images using spatial and transform domain techniques

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An Efficient DWT and Intuitionistic Fuzzy Based Multimodality Medical Image Fusion

An Efficient DWT and Intuitionistic Fuzzy Based Multimodality Medical Image Fusion

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