高光谱图像处理
导入、导出、处理和可视化高光谱数据
Image Processing Toolbox™ Hyperspectral Imaging Library 为高光谱图像处理和可视化提供 MATLAB® 函数和工具。
使用此库中的函数可读取、写入和处理通过使用高光谱成像传感器以各种文件格式捕获的高光谱数据。该库支持国家图像传输格式 (NITF)、可视化图像环境 (ENVI)、标记图像文件格式 (TIFF) 和元数据文本扩展 (MTL) 文件格式。
该库提供一套算法,用于端元提取、丰度图估计、辐射和大气校正、降维、波段选择、光谱匹配和异常检测。
高光谱查看器使您能够读取高光谱数据,可视化单个波段图像及其直方图,为高光谱数据立方体中的像素或区域创建光谱图,生成高光谱图像的不同的彩色或假彩色表示,以及显示元数据。
要执行高光谱图像分析,请从附加功能资源管理器下载 Image Processing Toolbox Hyperspectral Imaging Library。有关下载附加功能的详细信息,请参阅获取和管理附加功能。
App
高光谱查看器 | 可视化高光谱数据 (自 R2020a 起) |
函数
主题
快速入门
- Getting Started with Hyperspectral Image Processing
Basics of hyperspectral image processing. - Explore Hyperspectral Data in the Hyperspectral Viewer
This example shows how to explore hyperspectral data using the 高光谱查看器 app. - Process Large Hyperspectral Images
This example shows how to process small regions of large hyperspectral images. - Hyperspectral Data Correction
Describes radiometric calibration, atmospheric correction, and spectral correction. - Spectral Matching and Target Detection Techniques
Techniques for target detection and spectral matching. - Spectral Indices
Describes spectral indices. - Support for Singleton Dimensions
Analysis of 1-D and 2-D spectral data using singleton hypercube.
分类
- Classify Hyperspectral Image Using Library Signatures and SAM
Classify pixels in a hyperspectral image by using the spectral angle mapper (SAM) classification algorithm. - Classify Hyperspectral Images Using Deep Learning
This example shows how to classify hyperspectral images using a custom spectral convolution neural network (CSCNN) for classification. - Classify Hyperspectral Image Using Support Vector Machine Classifier
This example shows how to preprocess a hyperspectral image and classify it using a support vector machine (SVM) classifier.
区域标识
- Target Detection Using Spectral Signature Matching
Detect a known target in the hyperspectral image by using the spectral matching method. - Identify Vegetation Regions Using Interactive NDVI Thresholding
Identify the types of vegetations regions in a hyperspectral image through interactive thresholding of a normalized difference vegetation index (NDVI) map. - Find Regions in Spatially Referenced Multispectral Image
This example shows how to identify water and vegetation regions in a Landsat 8 multispectral image and spatially reference the image.