Image Fusion Using Laplacian Pyramid

In this paper, we implement image fusion using the Laplacian pyramid technique. The core algorithm involves constructing Gaussian and Laplacian pyramids for source images, then applying fusion rules at different pyramid levels. For infrared-visible image fusion, we combine thermal radiation information from infrared images with texture details from visible light images to generate comprehensive composite images with enhanced information content. The implementation typically uses pyramid decomposition with 4-6 levels and weighted fusion rules at each frequency band.

Additionally, we explore multi-focus image fusion methodology where multiple images with different focal points are integrated. The Laplacian pyramid approach effectively preserves in-focus regions from each source image while maintaining smooth transitions between fused areas. Key functions include pyramid construction using cv2.pyrDown()/pyrUp() in OpenCV, fusion rule application at each pyramid level, and pyramid reconstruction through progressive upsampling and combination.

These techniques have significant applications in medical imaging processing, military reconnaissance, and environmental monitoring domains, providing improved image clarity and information accuracy through multi-source data integration.