customSpectralIndex
Syntax
Description
Custom spectral indices can ease workflows where standard spectral indices are not applicable. You can use a custom spectral index to define and compute an index specific to your application. You can also use a custom spectral index to fine-tune commonly used spectral indices to your specific hyperspectral or multispectral data.
indexImage = customSpectralIndex(spcube,wavelengths,func)func. The formula uses the specified wavelengths,
wavelengths, in the hyperspectral or multispectral data
spcube.
indexImage = customSpectralIndex(spcube,wavelengths,func,BlockSize=blocksize)blocksize, for block processing of the
spectral data.
The function divides the input image into distinct blocks,
processes each block, and then concatenates the processed output of each block to form the
output matrix. Spectral images are multi-dimensional data sets that can be too large to fit in
system memory in their entirety. This can cause the system to run out of memory while running
the customSpectralIndex function. If you encounter such an issue, perform block
processing by using this syntax.
For example, customSpectralIndex(spcube,wavelengths,func,BlockSize=[50
50]) divides the input image into non-overlapping blocks of size 50-by-50 and
then computes the custom spectral index for pixels in each block.
Note
This function requires the Hyperspectral Imaging Library for Image Processing Toolbox™. You can install the Hyperspectral Imaging Library for Image Processing Toolbox from Add-On Explorer. For more information about installing add-ons, see Get and Manage Add-Ons.
The Hyperspectral Imaging Library for Image Processing Toolbox requires desktop MATLAB®, as MATLAB Online™ and MATLAB Mobile™ do not support the library.
Examples
Load a hyperspectral image into the workspace.
hcube = imhypercube("jasperRidge2_R198.img"); Colorize the hyperspectral image to get an RGB image.
rgbImg = colorize(hcube,Method="rgb",ContrastStretching=true);You can use the wavelengths in the green band and the short-wave infrared (SWIR) band to estimate the position of a water body in the hyperspectral image. The range of wavelengths of the green band is 500–600 nm, while the range of wavelengths of the SWIR band is 1550–1750 nm. Find the wavelengths in the hyperspectral image closest to the midpoints of the green band and the SWIR band.
AllWavelengths = hcube.Wavelength; GreenRange = [500 600]; [~,GreenIdx] = min(abs(AllWavelengths-mean(GreenRange))); GreenWavelength = AllWavelengths(GreenIdx); SWIRRange = [1550 1750]; [~,SWIRIdx] = min(abs(AllWavelengths-mean(SWIRRange))); SWIRWavelength = AllWavelengths(SWIRIdx); wavelengths = [GreenWavelength SWIRWavelength];
Create a function handle for a custom spectral index formula to estimate a water body from the green band and SWIR band wavelengths.
func = @(green,swir) (green-swir)./(green+swir);
Apply the custom water estimation formula to the hyperspectral image to get the water body index image.
waterImg = customSpectralIndex(hcube,wavelengths,func);
Threshold the water body index image to get a water body mask. Index values greater than 0.5 indicate open water bodies.
waterMask = waterImg > 0.5;
Overlay the water body mask on the RGB image.
overlayImg = imoverlay(rgbImg,waterMask,"b");Visualize the original RGB image, the water body index image, and the water body mask overlaid on the RGB image.
figure t = tiledlayout(1,3); t.TileSpacing = "compact"; t.Padding = "compact"; nexttile imshow(rgbImg) title("RGB Image") nexttile imagesc(waterImg) colorbar axis image off title("Water Body Index Image") nexttile imagesc(overlayImg) axis image off title("Overlay Image")
