A Detailed Analysis of Wavelet based Multi-Focus Image Fusion Techniques

Image fusion combines multiple images of a single scene or object, captured by various sensors or from different angles, to create an enhanced composite image with greater informational content. This process has applications across diverse fields, including remote sensing, medical diagnostics, security systems, robotics, augmented reality, and stereovision. Its primary objectives include improving visual details, overall image quality, and offering novel perspectives. Among the various fusion methods, wavelet-based techniques have gained popularity due to their ability to preserve crucial details, minimize noise, and enhance visual quality. This study aims to compare the efficacy of eight distinct wavelet-based multi-focus image fusion approaches. To assess the spectral and spatial characteristics of the resulting fused images, the research employs eight performance metrics, providing a comprehensive analysis of these techniques. The findings of this comparative study are important for deciding which method is the simplest, most effective, and fastest to produce high-quality merged images. This will enable it to be used with a variety of imaging modalities, especially those that have limited hardware resources or produce images with a high level of quality.