Evaluation of Image Fusion Results

This document provides detailed information about evaluation parameters for image fusion results. These parameters serve to assess various image characteristics and quality metrics. By implementing these evaluation metrics in MATLAB code, we can comprehensively analyze the performance and effectiveness of image fusion outcomes. The evaluation framework includes multiple approaches such as pixel-level assessment (implementing metrics like mutual information and root mean square error), structural similarity evaluation (using SSIM index algorithms), and information entropy analysis (calculating entropy values through histogram processing). Through systematic analysis of these evaluation parameters using corresponding MATLAB functions, we can effectively judge the advantages and limitations of different image fusion algorithms, as well as their practical applicability in real-world scenarios. The code implementation typically involves matrix operations for pixel-level calculations, statistical functions for quality metrics, and image processing toolboxes for feature extraction.