Wavelet Transform-Based Remote Sensing Image Fusion

This implementation uses MATLAB programming language to achieve wavelet transform-based remote sensing image fusion, a highly valuable method in the field of remote sensing image processing. The algorithm typically involves key MATLAB functions such as wavedec2 for 2D wavelet decomposition and waverec2 for reconstruction. Through wavelet transform, multiple remote sensing images can be effectively fused to produce clearer and more accurate results. The transform extracts detailed information from images and integrates features across different scales, significantly improving image quality and resolution. The implementation generally follows these steps: 1) Decompose input images into wavelet coefficients using multi-level decomposition, 2) Apply fusion rules (such as maximum selection or weighted average) to approximation and detail coefficients, 3) Reconstruct the fused image from the combined coefficients. Therefore, developing and applying wavelet transform-based remote sensing image fusion algorithms in MATLAB is highly worthwhile for exploration and practical implementation in image enhancement applications.