Explore MATLAB source code curated for "图像" with clean implementations, documentation, and examples.
Implementation of 3D reconstruction from point cloud data using MATLAB, featuring multiple examples and various point cloud images with excellent reconstruction results. The implementation covers point cloud processing, surface reconstruction algorithms, and visualization techniques.
Vortex beams represent a cutting-edge research field in optics. Under the guidance of leading domestic scholars, I conducted extensive research focusing on liquid crystal spatial light modulators (SLMs). This work successfully demonstrated various image displays including multiple types of vortex beams, interference patterns between vortex beams and plane waves, vortex-spherical wave interference, and self-interference of vortex beams. Below are selected code implementations available for download, featuring comprehensive algorithm descriptions and implementation approaches.
This program implements 3D reconstruction of objects using MATLAB, employing a methodology that first calibrates the camera to establish the relationship between the image coordinate system and world coordinate system. The system then reconstructs 3D information from multiple 2D images. The package includes MATLAB source code (.m files) and reconstruction images in JPG format, featuring camera calibration algorithms and stereo vision techniques.
Techniques for reading images in various formats and displaying indexed images with implementation examples.
Implementation of image and video denoising using sparse 3D transform-domain collaborative filtering with block-matching, transform coefficient shrinkage, and aggregation techniques
MATLAB implementation of Lee filter algorithm for effective speckle noise reduction in SAR imagery with configurable parameters
Generate and visualize white noise signal images using MATLAB with comprehensive implementation approaches
MATLAB implementation of 1D PCA for image compression and decompression with configurable number of eigenvalues to observe compression results. Demonstrates image preprocessing steps and PCA workflow.
This attachment contains MATLAB source code for image sparse representation, featuring fully functional implementation with configurable parameters for optimized performance across various image types.
MATLAB implementation for creating rectangular pulse signal waveforms with code examples