MATLAB Image Registration Code Implementation
MATLAB source code for image registration, designed for beginners to study together. This package contains comprehensive image registration programs collected from various online sources.
Explore MATLAB source code curated for "图像配准" with clean implementations, documentation, and examples.
MATLAB source code for image registration, designed for beginners to study together. This package contains comprehensive image registration programs collected from various online sources.
This program implements an image registration approach using wavelet transform for contour extraction. The algorithm first detects image edges through wavelet transformation, identifies the longest contour segment, computes curvature at each point along the contour, and performs data matching to determine optimal transformation parameters for precise image alignment. Key implementation involves multi-scale edge detection, curvature calculation algorithms, and feature-based matching techniques.
Implementation of normalized mutual information calculation method for two images in image registration, including algorithm explanation and key function descriptions
A comprehensive MATLAB digital image processing case study demonstrating image registration techniques using both feature points and feature regions, with detailed code implementation examples and algorithm explanations.
Source code for image registration based on mutual information, implementing particle swarm optimization algorithm with detailed similarity evaluation methods
A MATLAB-based image registration algorithm using contour features and maximum mutual information for accurate image alignment.
Image registration focusing on rotation and translation transformations, achieved through mutual information optimization with practical MATLAB code examples including key functions like imregister() and imtransform().
MATLAB-based implementation of image registration employing Gaussian optical flow technique for motion estimation and alignment
MATLAB source code for computing homography matrices, suitable for computer vision applications like image registration. The implementation includes point correspondence matching and robust estimation techniques.
The Demons algorithm is widely used for image registration, particularly in medical imaging, achieving high precision through gradient-based deformation field optimization with efficient computational implementation.