Contrast Pyramid-Based Image Fusion Algorithm

This program implements a contrast pyramid-based image fusion algorithm that delivers satisfactory performance and serves as a practical reference. The algorithm works by decomposing multiple input images at different scales using Laplacian or Gaussian pyramid decomposition, analyzing contrast differences at each pyramid level, and then reconstructing the fused image through pyramid synthesis. During implementation, key functions typically include pyramid construction using cv2.pyrDown()/pyrUp() for scale-space decomposition, contrast calculation through local variance or gradient magnitude analysis, and fusion rule application at each pyramid level. The method effectively enhances image quality and detail preservation by combining the best features from source images, demonstrating significant improvements in fusion outcomes. Furthermore, the algorithm exhibits strong robustness and stability through its multi-scale approach, making it suitable for various image fusion tasks including medical imaging, remote sensing, and computational photography. For researchers and developers working on image fusion applications, this implementation provides a reliable reference model with well-structured code organization featuring modular pyramid processing and configurable fusion rules.