Review of Various Image Fusion Algorithms and Image Fusion Performance Metric

• Published in: Archives of computational methods in engineering Vol. 28; no. 5; pp. 3645 - 3659
• Main Authors: Singh, Simrandeep, Mittal, Nitin, Singh, Harbinder
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.08.2021; Springer Nature B.V
• Subjects: Algorithms; Computed tomography; Computer vision; Domains; Engineering; Image processing; Infrared detectors; Mathematical and Computational Engineering; Medical imaging; Original Paper; Performance evaluation; Positron emission; Remote sensing; Satellite imagery; Sensors; Tomography
• ISSN: 1134-3060; 1886-1784
• DOI: 10.1007/s11831-020-09518-x

Image fusion is the process in which substantial information taken through different sensors, different exposure values and at different focus points is integrated together to generate a composite image. In various applications, different types of data sets are captured with the help of different sensors like infrared (IR) region and visible region, Computed Tomography (CT) and Positron Emission Tomograph (PET) scan, multifocus images with different focal points and images taken by a static camera at different exposure values. A most promising area of image processing nowadays is image fusion. The picture fusion method seeks to incorporate two or more pictures into one picture that contains better data than each source picture without adding any artifacts. It plays an essential role in distinct applications like biomedical diagnostics, photography, object identification, surveillance, defense, and remote sensing satellite imaging. Three elements are taken into consideration in this review article that includes spatial domain fusion methodology, different transformation domain techniques, and image fusion performance evaluation metrics.