Explore MATLAB source code curated for "颜色空间" with clean implementations, documentation, and examples.
This method implements K-means clustering algorithm in LAB color space for image segmentation combined with Hough transform for circle detection, providing a comprehensive approach to circular object identification in digital images.
A MATLAB program for calculating Gray-Level Co-occurrence Matrix (GLCM) with eight-dimensional texture feature extraction, referenced from "Image Retrieval Based on Color Space and Texture Features." This implementation processes input image data and returns an 8D texture feature row vector suitable for image analysis and retrieval systems.
Implementation of image inpainting suitable for large damaged areas. This algorithm utilizes exemplar-based image inpainting for region filling and object removal, operates in CIE Lab color space for improved color perception alignment, and was originally published in IEEE 2004. The MATLAB implementation includes priority-based patch selection and texture synthesis mechanisms.
Implementation of HSI to RGB color space conversion using MATLAB with algorithm explanation and practical applications.
Perform color space segmentation on images followed by cluster analysis. The code is straightforward and ready to execute, utilizing algorithms like K-means for color clustering with practical implementation insights.
Computational Methods for Color Difference Measurement with Implementation Details