Custom Wavelet Transform-Based Image Fusion Program

This program implements wavelet transform-based image fusion using custom-developed code. It supports multi-level wavelet decomposition of images, allowing users to merge multiple source images into a single, clearer image with enhanced detail representation. The wavelet transform method effectively processes images by decomposing them into frequency sub-bands, extracting multi-scale detail information for optimized fusion results. Key implementation features include configurable decomposition levels through parameterized function calls, where users can specify the number of decomposition layers according to their requirements. The core algorithm employs wavelet decomposition functions (like dwt2 for 2D discrete wavelet transform) and fusion rules for combining approximation and detail coefficients. The program architecture includes coefficient selection methods for combining high-frequency components and weighted average fusion for low-frequency components. The system features an intuitive GUI interface built using MATLAB's App Designer or similar frameworks, providing user-friendly controls for image selection, parameter adjustment, and real-time result preview. Even users unfamiliar with image processing can easily operate the program through its guided workflow. Underlying optimization techniques ensure computational efficiency, including vectorized operations for wavelet computations and optimized memory handling for large image datasets. The implementation achieves fast processing speeds through algorithm optimization, typically completing fusion tasks within seconds depending on image size and decomposition levels. In summary, this wavelet-based image fusion program represents a robust, user-friendly tool with high-performance processing capabilities, suitable for various image enhancement applications in research and practical implementations.