![]() ![]() The test data contains nine endmembers that represent these ground truth classes: Asphalt, Meadows, Gravel, Trees, Painted metal sheets, Bare soil, Bitumen, Self blocking bricks, and Shadows. There are other parameters for generating call trees and such, not sure if they work with the converted MatLab code. Be sure to set EXTRACTALL YES to get auto-generated documentation for code without comments. This example uses a data sample from the Pavia University dataset as test data. 4 You can use doxygen plus an appropriate filter, such as UsingDoxygenwithMatlab. The Image Processing Toolbox Hyperspectral Imaging Library requires desktop MATLAB®, as MATLAB® Online™ and MATLAB® Mobile™ do not support the library. For more information about installing add-ons, see Get and Manage Add-Ons. References between images in total, regions of images, annotations regarding the images, and other media, are achieved by means of hyperlinks. ![]() You can install the Image Processing Toolbox Hyperspectral Imaging Library from Add-On Explorer. The HyperImage platform supports the linking of (audio)-visual objects, texts and mixed-media documents. This example requires the Image Processing Toolbox™ Hyperspectral Imaging Library. In this example, you will classify the pixels in a hyperspectral image by finding the maximum abundance value for each pixel and assigning it to the associated endmember class. The set of abundance values obtained for each pixel represents the percentage of each endmembers present in that pixel. Use the object functions to remove or select a desired hyperspectral band, assign new pixels values, generate colored image, and write hyperspectral data to the ENVI (environment for visualizing images) file format. Each pixel in the image is either a pure pixel or a mixed pixel. An abundance map characterizes the distribution of an endmember across a hyperspectral image. Answers (0) Sign in to answer this question. This example shows how to identify different regions in a hyperspectral image by performing maximum abundance classification (MAC). Walter Roberson on Theme Copy cat (3, firstband, secondband, thirdband) but since all of your data is probably in a 3D array, just extract Theme Copy bands 17 53 58 for example combinedbands YourHyperImage (:, :, bands) Sign in to comment. ![]()
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