Multi-band Image Fusion

Multi-band image fusion is a common application in image processing, particularly when implemented using MATLAB programming. This technique combines images from different sensors or spectral bands to generate more comprehensive and accurate visual information. In this example, we can develop a MATLAB program for multi-band image fusion that integrates and enhances images through algorithmic processing. By merging images from different spectral bands, we obtain richer and more detailed composite images, providing enhanced information and superior visual quality.

The implementation typically involves reading multiple input images, preprocessing them for alignment and normalization, applying fusion algorithms such as wavelet transform, principal component analysis (PCA), or intensity-hue-saturation (IHS) transformation, and generating the final fused output. Key MATLAB functions used may include imread() for image loading, rgb2gray() for conversion, imfuse() for basic fusion operations, and custom wavelet functions for advanced multi-resolution analysis. The fusion process improves features like spatial resolution, spectral preservation, and contrast enhancement, making it valuable for remote sensing, medical imaging, and computer vision applications.