MATLAB Code for Spatial Transformation in Image Fusion

This MATLAB code implements spatial transformation for image fusion processes. The algorithm performs fusion between two images by applying coordinate transformations and feature alignment techniques. Spatial transformation serves as a critical preprocessing step in image fusion, enabling effective matching and adjustment of features from different source images to achieve optimal blending results. The implementation likely utilizes MATLAB's image processing toolbox functions such as imwarp for geometric transformations, and may incorporate interpolation methods (nearest-neighbor, bilinear, or bicubic) for pixel value estimation during spatial mapping. Key components may include affine or projective transformations to align image features, followed by fusion operations like weighted averaging or pyramid-based blending. This code provides researchers and developers with flexible control over fusion parameters, allowing customization of transformation matrices and fusion rules to achieve desired visual outcomes. The implementation demonstrates practical applications in medical imaging, remote sensing, and computer vision where multi-source image integration is required. The code structure typically involves: 1. Input image preprocessing and normalization 2. Spatial transformation parameter calculation 3. Coordinate mapping and interpolation operations 4. Fusion operation implementation 5. Result evaluation and output generation This resource serves as a valuable reference for image processing professionals working on multi-modal image integration projects.