Wavelet Image Fusion MATLAB Code Implementation

The waveletimfusion is a MATLAB code implementation for wavelet-based image fusion. It employs wavelet transform and fusion algorithms to generate fused images from multiple source images, with built-in objective analysis capabilities to evaluate fusion performance. Wavelet image fusion is a widely-used technique in image processing that combines multiple images into a single composite image to extract enhanced information content.

This implementation provides a comprehensive framework for wavelet-based image fusion, typically involving these key processing stages: First, the source images undergo multi-level wavelet decomposition using filters like Daubechies or Symlets. The code then applies fusion rules (such as maximum selection, weighted average, or region-based fusion) to combine wavelet coefficients from different source images. Common approaches include fusing low-frequency coefficients using averaging methods while selecting high-frequency coefficients based on activity level measurements. After coefficient fusion, the inverse wavelet transform reconstructs the final fused image.

The package includes objective evaluation metrics like mutual information, structural similarity index (SSIM), and fusion quality indices to quantitatively assess fusion performance. Key MATLAB functions likely include wavelet decomposition (wavedec2), coefficient processing, and reconstruction (waverec2) functions, along with custom fusion rule implementations. Users can easily modify fusion rules and wavelet parameters to adapt to specific application requirements.

Through waveletimfusion, researchers and engineers can efficiently implement image fusion workflows, analyze fusion results using both visual inspection and quantitative metrics, and optimize parameters for different multi-image fusion scenarios such as medical imaging, remote sensing, and surveillance applications.