Implementation of Image Fusion Algorithm Using Wavelet Frame

This implementation utilizes wavelet frames to achieve image fusion, a technique that enhances image quality by combining two or more source images into a single composite image. The algorithm involves three key stages: first, preprocessing both input images to ensure compatibility; second, performing wavelet frame decomposition to transform images into wavelet domain representations; and finally, synthesizing a new image through weighted averaging of wavelet coefficients from different source images.

The package includes several test images that can be used to evaluate the fusion algorithm's performance. These images serve as benchmarks for comparing different fusion approaches and selecting optimal algorithms for specific applications. Developers can also utilize their own custom images to test the algorithm's adaptability to particular use cases. The implementation typically employs discrete wavelet transform functions for decomposition and reconstruction, with coefficient weighting strategies that may include maximum selection, average weighting, or region-based fusion rules.