Explore MATLAB source code curated for "高光谱图像处理" with clean implementations, documentation, and examples.
This graduation project focuses on fundamental hyperspectral image processing, implementing core functionalities including single-band extraction and pseudo-color image synthesis. The project provides a modular program framework that allows easy integration of additional features. A MATLAB-based GUI interface has been developed to enhance user interaction and operational efficiency.
A MATLAB-based program toolbox for hyperspectral image processing, featuring a comprehensive GUI toolbox that enables convenient and efficient manipulation of hyperspectral imaging data through intuitive graphical interfaces and algorithmic implementations.
Minimum Noise Fraction Transformation Method for Hyperspectral Image Processing with Implementation Approaches
Endmember extraction for hyperspectral image processing where the PPI (Pixel Purity Index) method efficiently extracts endmember spectra with geometric projection and iterative refinement approaches.
Self-developed PCA function for hyperspectral image processing using MATLAB implementation, primarily designed for dimensionality reduction with customizable code structure for various analytical requirements.
Comprehensive MATLAB programs for hyperspectral image processing featuring image fusion, dimensionality reduction, and maximum likelihood classification algorithms with practical implementation examples
A MATLAB-based SVM toolkit designed for image processing and hyperspectral image analysis, featuring implementation of core classification algorithms and spectral data handling capabilities.