Explore MATLAB source code curated for "图像" with clean implementations, documentation, and examples.
Implementation of optimal automatic image threshold segmentation using MATLAB source code, featuring the commonly used Otsu's method algorithm for efficient image partitioning
Registration of Two Images Using Mutual Information as a Similarity Measure
The MATLAB environment for 3D image reconstruction supports processing and analysis of various image types through specialized toolboxes and algorithmic implementations.
MATLAB Implementation of Gray-Level Co-occurrence Matrix - The joint probability matrix method statistically surveys all pixels in an image to describe its gray-level distribution. This implementation calculates spatial relationships between pixel pairs to extract texture features for image analysis.
A program implementing SIFT algorithm for feature matching, which detects keypoints and establishes correspondences between keypoints in two images. The implementation includes sample images demonstrating excellent matching results with techniques for scale-space extrema detection and descriptor generation.
Implementing Huffman Coding in MATLAB for Lossless Image Compression with Pixel Frequency Analysis and Encoding Techniques
MATLAB program implementing K-means clustering algorithm for image segmentation with pixel classification capabilities
Implementing three-level wavelet decomposition on images to separate them into different frequency sub-bands and extract corresponding coefficients, with code implementation details for wavelet transformation and coefficient analysis.
MATLAB implementation of image sharpening techniques using various operators including Sobel, Laplacian, and Prewitt filters for edge enhancement and detail processing
Linear Discriminant Analysis (LDA) for feature selection enables extraction of discriminative features from datasets or images, commonly applied in machine learning tasks such as classification or clustering. The method involves maximizing class separability through dimensionality reduction.