An image plays a vital role in today's environment. An image is a visual representation of anything that can be used in the future for recollecting or memorizing that scene. This visual representation is created by recording the scene through an optical device like a camera or mobile phone. The image fusion process helps integrate relevant data of the different images in a process into a single image. Image fusion applications are wide in range, and so is the fusion technique. In general, pixel, feature, and decision-based techniques for picture fusion are characterised. This study's main thrust is the application and comparison of two approaches to the image fusion process: PCA (principal component analysis) and CNN (convolutional neural network).The study implemented a practical approach to MATLAB. The result of the study is that CNN is much more favorable in terms of image quality and clarity but less favorable in terms of time and cost.
Authors: Ashi Agarwal, Binay Kumar Pandey, Poonam Devi, Sunil Kumar, Mukundan Appadurai Paramashivan, Ritesh Agarwal, Pankaj Dadheech
DOI: https://doi.org/10.4018/978-1-6684-8618-4.ch012
Publish Year: 2023
