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高光谱图像处理 -凯发k8网页登录

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、条带选择、光谱匹配和异常检测。

使您能够读取高光谱数据，可视化单个条带图像及其直方图，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。

app

可视化高光谱数据

函数

读取和写入

read hyperspectral data
write hyperspectral data to envi file format
read metadata from envi header file

条带选择和条带删除

select most informative bands
remove spectral bands from data cube

roi 选择

assign new data to hyperspectral data cube
crop regions-of-interest

颜色变换

estimate color image of hyperspectral data
denoise hyperspectral images using non-local meets global approach
sharpen hyperspectral data using coupled nonnegative matrix factorization (cnmf) method

辐射标定

convert digital number to radiance
convert digital number to reflectance
convert radiance to reflectance

大气校正

correct out-of-band effect using sensor spectral response
empirical line calibration of hyperspectral data
perform fast in-scene atmospheric correction
apply flat field correction to hyperspectral data cube
apply internal average relative reflectance (iarr) correction to hyperspectral data cube
apply log residual correction to hyperspectral data cube
compute remote sensing reflectance
subtract dark pixel value from hyperspectral data cube
perform atmospheric correction using satellite hypercube atmospheric rapid correction (sharc)

频谱校正

compute spectral smile metrics of hyperspectral data
reduce spectral smile effect in hyperspectral data cube
principal component analysis of hyperspectral data
maximum noise fraction transform of hyperspectral data
reconstruct data cube from principal component bands
extract endmember signatures using pixel purity index
extract endmember signatures using fast iterative pixel purity index
extract endmember signatures using n-findr
find number of endmembers
estimate abundance maps
read data from ecostress spectral library
measure spectral similarity using spectral angle mapper
measure spectral similarity using spectral information divergence
measure spectral similarity using jeffries matusita-spectral angle mapper method
measure spectral similarity using spectral information divergence-spectral angle mapper hybrid method
measure normalized spectral similarity score
identify unknown regions or materials using spectral library
compute hyperspectral indices
normalized difference vegetation index
detect anomalies using reed-xiaoli detector

主题


  • basics of hyperspectral image processing.


  • this example shows how to explore hyperspectral data using the 高光谱查看器 app.


  • describes radiometric calibration and atmospheric correction.


  • describes spectral indices.


  • analysis of 1d and 2d spectral data using singleton hypercube.

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