Explore MATLAB source code curated for "图象处理" with clean implementations, documentation, and examples.
Image Processing: Compute connected component metrics including area, perimeter, circularity, rectangularity, and aspect ratio, with implementation using regionprops function and custom calculations
A doctoral-researcher developed toolkit for PDE-based image processing. Highly practical and beneficial for professionals working with partial differential equations in image analysis. Includes implementations of key algorithms like Perona-Malik diffusion and variational methods.
Adaptive thresholding image processing with iterative calculation implementation
This source code written by an international Master's graduate contains valuable insights on iris biometric extraction, particularly noteworthy for image processing researchers due to its robust feature detection methodology and efficient algorithm design.
Image extraction and interpolation are frequently used in image processing; this program implements the widely adopted bilinear interpolation algorithm with code examples for pixel value calculation.
MATLAB implementation of the T algorithm applying center-weighted median filtering to images with comparison between original and processed images, including filter parameter configuration and difference analysis techniques.
This repository contains the companion source code for "Adaptive Blind Signal and Image Processing" (Chinese title: 《自适应盲信号与图象处理》) authored by Andrzej Cichocki and Shun-ichi Amari (Japan), published in 2005. This book represents the most systematic and up-to-date resource on blind signal and image processing, featuring MATLAB implementations of key algorithms such as Independent Component Analysis (ICA), blind source separation, and adaptive filtering techniques.
Comprehensive MATLAB source code implementing the contourlet transform and its associated utility functions for advanced image processing applications. This implementation follows the algorithm described in the seminal paper "The Contourlet Transform: An Efficient Directional Multiresolution Image Representation" included in the package, featuring directional filter banks and multiscale decomposition capabilities.
Input: x: input image, ru, rd: row extension amounts (up and down), cl, cr: column extension amounts (left and right), extmod: extension mode. Valid extension modes include: Primarily used for image processing and pattern recognition applications with border handling implementations.
This comprehensive MATLAB-based toolkit provides robust implementations for various audio and image processing tasks. The audio processing module includes Linear Predictive Coding (LPC), Fast Fourier Transform (FFT), formant analysis, and spectral processing with complete source code. The image processing component offers multiple algorithms with detailed reference implementations. The package features an intuitive GUI interface for easy operation and customization.