Two-dimensional Chebyshev polynomials for image fusion

Abstract

This report documents in detail the research carried out by the author throughout his first year. The paper presents a novel method for fusing images in a domain concerning multiple sensors and modalities. Using Chebyshev polynomials as basis functions, the image is decomposed to perform fusion at feature level. Results show favourable performance compared to previous efforts on image fusion, namely ICA and DT-CWT, in noise affected images. The work presented here aims at providing a novel framework for future studies in image analysis and may introduce innovations in the fields of surveillance, medical imaging and remote sensing.