Explore MATLAB source code curated for "图像处理" with clean implementations, documentation, and examples.
GUI interface design for general image processing operations including rotation, noise addition, histogram equalization, and advanced techniques with MATLAB implementation details
Source code implementation for sparse decomposition in signal and image processing, featuring comprehensive documentation and algorithmic explanations in a WORD document format
A MATLAB-based vehicle type recognition program that identifies buses, sedans, vans, and other vehicle types using background subtraction for vehicle region detection followed by advanced image processing techniques
MATLAB Image Processing: Comprehensive Guide to Image Segmentation and Edge Detection Algorithms with Implementation Examples
Independent Component Analysis (ICA) is a powerful data analysis tool that has emerged in recent years. It was first mathematically defined by Comon in 1994, building upon concepts originally introduced by Herault and Jutten in 1986. Despite its relatively recent development, ICA has gained significant theoretical and practical attention globally, becoming a prominent research focus. Its implementation typically involves optimization algorithms like FastICA or InfoMax to separate statistically independent source signals from mixed observations. Applications span blind source separation, image processing, speech recognition, biomedical signal processing, and financial data analysis, making it an extension of Principal Component Analysis (PCA) with broader independence constraints.
A MATLAB-based source code collection for image processing, featuring implementations for thresholding, binarization, grayscale transformations, edge detection, and various other fundamental operations with algorithm-specific optimizations.
Median filtering is an effective digital image processing technique for eliminating noise from images. Our implementation allows you to run the code on your images for further processing. You can apply median filters with various kernel sizes including 3x3, 5x5, 7x7, and 9x9 - larger kernel sizes typically yield better noise reduction results by considering broader pixel neighborhoods.
Image processing source code for various operations including image interpolation, image restoration, and image enhancement with detailed algorithmic implementation
MATLAB source code for fundamental 3D matching algorithms, featuring image processing techniques and 3D reconstruction capabilities with practical implementation examples
Kevin Murphy's MATLAB toolkit for Conditional Random Fields (CRF) enables advanced probabilistic modeling with applications in image processing and beyond, featuring flexible graph structures and efficient inference algorithms.