A Primer on Super Resolution for Images and Video
Introduction to Super Resolution Techniques for Images and Video - Ideal entry-level book covering fundamental concepts and practical implementations with code examples
Explore MATLAB source code curated for "图像" with clean implementations, documentation, and examples.
Introduction to Super Resolution Techniques for Images and Video - Ideal entry-level book covering fundamental concepts and practical implementations with code examples
This program first converts images from RGB color space to HSI color space, then employs color image segmentation strategies combined with the Mean Shift algorithm for image segmentation, followed by boundary synthesis. The 'keyprogram.m' file serves as the main program, while 'meanshift.m' contains the called function responsible for implementing data clustering segmentation through kernel density estimation and mode-seeking operations.
A practical communication interleaver program with proven effectiveness, designed to scatter concentrated errors in images through systematic data redistribution
This code implements image thresholding using fuzzy c-means clustering, demonstrating superior performance compared to traditional Otsu's method for various image types.
Implementation of mouse movement coordinate acquisition on images within MATLAB graphical user interface, with callback function integration and coordinate extraction techniques.
Implementation of Discrete Cosine Transform (DCT) high-pass and low-pass filters for image processing, with comparison to Fourier Transform (FFT) filtering. Visual results demonstrate that DCT low-pass filtering produces significant blurring due to energy reduction from taking the real component of FFT. DCT high-pass filtering removes low-frequency components, resulting in darkened images with only edge traces visible. Code implementation includes frequency domain masking and coefficient thresholding techniques.
This code implements straight line detection in images using Hough transform, featuring high efficiency and excellent detection performance through optimized parameter space analysis and peak detection algorithms.
Color extraction enables the retrieval of content-specific colors from various images, allowing for rapid isolation of distinct elements' chromatic properties with computational efficiency through algorithmic processing.
This program is designed for extracting symmetry axes from images or identifying symmetry axes of target objects within images, implementing advanced image processing algorithms for accurate axis detection.
Palmprint Recognition System V1: Identifies palmprints using eigenpalm-based methodology. The system functions by projecting palmprint images across significant variations in known image datasets. Features include: principal component analysis implementation, pattern recognition algorithms, and biometric authentication capabilities. Full MATLAB source code available at: http://matlabcode.com/palmprint-recognition-system-matlab-full-source-code/