Image Fusion Toolbox

This resource provides an image fusion toolbox with comprehensive MATLAB implementations for image processing tasks. The Image Fusion Toolbox serves as an essential utility that enables users to address various image processing requirements through standardized algorithms and functions. By leveraging this toolbox, users gain access to enhanced image processing capabilities including filtering operations (such as Gaussian and median filters), image enhancement techniques (like histogram equalization and contrast stretching), advanced fusion methods (including wavelet-based and PCA fusion algorithms), and segmentation approaches (such as region-growing and edge detection). The toolbox architecture allows straightforward implementation through simple function calls to predefined methods. For instance, users can execute image fusion using wavelet transforms by calling functions like wavelet_fusion() with configurable decomposition levels and fusion rules. Each module includes optimized MATLAB code with vectorized operations for efficient processing of image matrices. Additionally, the toolbox provides detailed documentation covering algorithm principles, parameter tuning guidelines, and practical examples demonstrating function usage. Sample scripts illustrate complete workflows, such as multi-focus image fusion using Laplacian pyramid decomposition with weighted average fusion rules. The included validation datasets and performance metrics (including mutual information and structural similarity indices) facilitate method evaluation. Whether for educational purposes in understanding image processing fundamentals or for practical applications in medical imaging, remote sensing, or computer vision projects, this Image Fusion Toolbox represents an indispensable resource with professionally implemented MATLAB functions and thorough technical support materials.