Window-Based Tool for Image Fusion

Image fusion is a crucial technique in computer vision and image processing that combines multiple source images to generate a more informative composite result. The window-based tool simplifies this process through a graphical user interface, enabling intuitive operation without requiring users to write complex code manually.

Among common fusion algorithms, PCA (Principal Component Analysis) fusion extracts dominant information components based on statistical characteristics, suitable for scenarios demanding high spectral preservation. IHS fusion enhances the integration of multispectral and panchromatic images through color space transformation. Pyramid fusion and wavelet transforms decompose and reconstruct images at different scales, preserving both high-frequency details and low-frequency structural information. Additionally, Brovey fusion rapidly enhances color information through mathematical ratio adjustments, making it ideal for remote sensing image processing.

The advantage of the window-based tool lies in its ability to eliminate manual parameter tuning and data format conversions. Users can directly select algorithms, adjust fusion weights, and preview results in real-time through the visual interface. This significantly lowers the application barrier for image fusion technology, making it accessible for research, remote sensing monitoring, medical imaging, and various other fields.