@inproceedings{aa679f2796714514bf95409bafe5e0fc,
title = "Infrared and Visible Image Fusion Objective Evaluation Method",
abstract = "Infrared{\textendash}visible (IR{\textendash}VIS) pixel level image fusion has been applied in many fields in which thermal measurements are used. This process provides spatial information about objects and invisible details to infrared images. In medical applications, infrared thermography provides information about physiology and is a supplement of classical diagnostic methods. The purpose of fusion in presented study was to improve human body thermograms. The novel objective fusion results comparison method, based on statistical analysis, has been proposed to indicate the best fusion method. Fusion methods were chosen based on literature and subjective assessment. Resulting images were parameterized with numerical fusion evaluation metrics. Obtained numerical values were cumulated to one parameter, corresponding to one image. These parameters were applied to compare results using Friedman test and post{\textendash}hoc 1 x N procedure.",
keywords = "Image fusion, Image registration, Infrared imaging, Multimodal imaging, Statistical analysis",
author = "Daniel Ledwo{\'n} and Jan Juszczyk and Ewa Pietka",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 7th International Conference on Information Technology in Biomedicine, ITIB 2019 ; Conference date: 18-06-2019 Through 20-06-2019",
year = "2019",
doi = "10.1007/978-3-030-23762-2\_24",
language = "English",
isbn = "9783030237615",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "268--279",
editor = "Ewa Pietka and Pawel Badura and Jacek Kawa and Wojciech Wieclawek",
booktitle = "Information Technology in Biomedicine, 2019",
address = "Germany",
}