Image Fusion and its Implementation with Source Code in MATLAB Environment

This article explores image fusion technology and its implementation within the MATLAB environment. Image fusion is a technique that combines multiple images into a single composite image to enhance both quality and information content. It finds extensive applications across various domains including medical imaging, computer vision, and remote sensing image analysis. This discussion covers the underlying principles and methodologies of image fusion, accompanied by practical MATLAB source code implementations. The provided code demonstrates key algorithms such as wavelet transform-based fusion, principal component analysis (PCA), and pyramid decomposition methods. Through these code examples, readers can gain deeper insights into fusion mechanisms, including pixel-level fusion techniques and feature extraction processes using MATLAB's Image Processing Toolbox functions like imfuse and custom wavelet functions. The implementation details include parameter optimization for different image types and fusion rules for combining coefficient maps. This hands-on approach enables readers to both understand the operational principles and adapt the code for further research and application-specific requirements.