Explore MATLAB source code curated for "图像融合" with clean implementations, documentation, and examples.
Principal Component Analysis demonstrates strong performance in image fusion applications, particularly excelling at spatial feature preservation while showing relatively weaker spectral characteristic retention, with implementation involving covariance matrix computation and eigenvalue decomposition.
An excellent introductory program for learning image fusion techniques, implementing image transformations, applying fusion strategies in the transform domain, and performing inverse transformations to complete the fusion process
Image Fusion Implementation in MATLAB. A robust solution using various algorithms including discrete wavelet transform and multi-scale decomposition techniques.
Image fusion program based on compressive sensing theory, implemented using MATLAB with optimized computational efficiency
A comprehensive MATLAB program for discrete wavelet transform-based image fusion capable of processing grayscale images in any format, featuring multi-level decomposition and customizable fusion rules
An image fusion program designed to extract high-resolution components from images and enhance image clarity through multi-scale decomposition and fusion algorithms
A MATLAB-based wavelet image fusion algorithm demonstrating significant performance improvements in image quality enhancement.
Comparative analysis of four image fusion techniques (IHS, PCA, Wavelet, and Wavelet-PCA Hybrid) between panchromatic and multispectral images, including implementation methods and evaluation metrics calculation (Information Entropy, Q4, etc.)
This program implements image feature extraction using the SIFT algorithm, followed by initial feature matching, outlier removal via Random Sample Consensus (RANSAC), and final image fusion to create seamless panoramic images.
Comprehensive image fusion programs including research implementations with detailed code descriptions covering pixel-level fusion, wavelet transforms, and deep learning methods for advanced image processing applications.