Explore MATLAB source code curated for "互信息" with clean implementations, documentation, and examples.
A complete set of 7 image fusion metrics including comprehensive entropy, spatial frequency, mutual information, and more! Tested with two source images - all algorithms are validated with excellent performance, delivering direct results.
This project implements image registration through initial preprocessing followed by dual registration criteria: mutual information and edge-based interactive variance, with code-level implementation details for both algorithms.
Image fusion metrics including comprehensive entropy, spatial frequency, mutual information and more - total 7 evaluation methods. These metrics are highly useful for quality assessment in image processing applications with MATLAB implementation examples.
A comprehensive MATLAB toolkit for mutual information theory, featuring algorithms for calculating mutual information, entropy, and related formulas, with detailed code implementations and mathematical foundations
Evaluation metrics for community detection, calculating mutual information for network partitions - higher values indicate more accurate community identification with implementation insights
An advanced image registration algorithm utilizing mutual information with hybrid optimization techniques
Several Image Fusion Evaluation Metrics with Implementation Insights
Comprehensive calculation methods for entropy, joint entropy, conditional entropy, and mutual information with code implementation considerations
Comprehensive metrics for evaluating image fusion quality and performance