The IHS Transformations Based Image Fusion

TL;DR

This paper explores various IHS transformation techniques for image fusion, evaluating their effectiveness in sharpening and information enhancement through quantitative performance metrics.

Contribution

It systematically compares different IHS transformations and assesses their impact on image fusion quality, clarifying inconsistencies in existing formulas.

Findings

Certain IHS transformations improve image sharpness

Some formulas lead to better information preservation

Quantitative metrics validate the effectiveness of selected methods

Abstract

The IHS sharpening technique is one of the most commonly used techniques for sharpening. Different transformations have been developed to transfer a color image from the RGB space to the IHS space. Through literature, it appears that, various scientists proposed alternative IHS transformations and many papers have reported good results whereas others show bad ones as will as not those obtained which the formula of IHS transformation were used. In addition to that, many papers show different formulas of transformation matrix such as IHS transformation. This leads to confusion what is the exact formula of the IHS transformation?. Therefore, the main purpose of this work is to explore different IHS transformation techniques and experiment it as IHS based image fusion. The image fusion performance was evaluated, in this study, using various methods to estimate the quality and degree of information improvement of a fused image quantitatively.