Image Fusion Based on Low-Frequency Fusion Algorithm and Wavelet Transform with MATLAB Implementation

This MATLAB program implements image fusion using a low-frequency fusion algorithm combined with wavelet transform, containing comprehensive wavelet image decomposition and reconstruction routines. The implementation employs wavelet decomposition to separate image components into different frequency bands, followed by specialized fusion rules for low-frequency coefficients to preserve essential image information. The program features high flexibility, allowing customization of wavelet types (such as Haar, Daubechies, or Symlets), decomposition levels, and fusion rules according to specific image requirements. Key functions include wavelet decomposition (wavedec2), coefficient fusion algorithms, and wavelet reconstruction (waverec2) to accurately capture and combine detail and edge characteristics from source images. Through intelligent fusion of high-frequency detail coefficients and optimized low-frequency component integration, the program generates output images with enhanced clarity and superior quality. Users can achieve improved image processing results and better satisfy their image enhancement needs through parameter adjustments and algorithm optimization.