Compressing hyperspectral data (hypercube)
Hyperspectral scene data (also called hypercube (HC)) can be quite large. The spectral functions in the data are typically smooth, and thus compressible.
Here, we use a linear model calculated from the singular value decomposition (svd) of the raw data to define spectral basis functions. We represent the image photons with respect to these spectral bases.
There are a number of functions that manage hyper-cube data. You can list these using
doc('hypercube')
See also: hcBasis, scenePlot, sceneFromFile, ieSaveMultiSpectralImage, s_scene2ImageData, s_scene2SampledScene, s_renderScene,
Copyright ImagEval Consultants, LLC, 2012
Contents
ieInit
delay = 0.2;
clear basis
Read in the scene
fName = fullfile(isetRootPath,'data','images','multispectral','StuffedAnimals_tungsten-hdrs'); scene = sceneFromFile(fName,'multispectral'); % Have a look at the image sceneWindow(scene); pause(delay); % Plot the illuminant scenePlot(scene,'illuminant photons');
Reading multispectral data with mcCOEF. Saved using svd method
Compress the hypercube requiring only 95% of the var explained
vExplained = 0.95;
[imgMean, imgBasis, coef] = hcBasis(sceneGet(scene,'photons'),vExplained);
Save the data
wave = sceneGet(scene,'wave'); basis.basis = imgBasis; basis.wave = wave; comment = 'Compressed using hcBasis with imgMean)'; illuminant = sceneGet(scene,'illuminant'); if (~exist(fullfile(isetRootPath,'local'),'dir')) mkdir(fullfile(isetRootPath,'local')); end oFile = fullfile(isetRootPath,'local','deleteMe.mat'); ieSaveMultiSpectralImage(oFile,coef,basis,comment,imgMean,illuminant);
read in the data
wList = 400:5:700; scene2 = sceneFromFile(oFile ,'multispectral',[],[],wList); % This poor representation produces a very desaturated % image sceneWindow(scene2); pause(delay);
Reading multispectral data with mcCOEF. Saved using svd method
Now require that much more of the variance be explained
vExplained = 0.99; [imgMean, imgBasis, coef] = hcBasis(sceneGet(scene,'photons'),vExplained); fprintf('Number of basis functions %.0f\n',size(imgBasis,2));
Number of basis functions 3
Save the data
wave = sceneGet(scene,'wave'); basis.basis = imgBasis; basis.wave = wave; comment = 'Compressed using hcBasis with imgMean)'; illuminant = sceneGet(scene,'illuminant'); % illuminant.wavelength = scene.spectrum.wave; % illuminant.data = scene.illuminant.data; ieSaveMultiSpectralImage(oFile,coef,basis,comment,imgMean,illuminant);
read in the data
wList = 400:5:700;
scene2 = sceneFromFile(oFile ,'multispectral',[],[],wList);
sceneWindow(scene2); pause(delay)
Reading multispectral data with mcCOEF. Saved using svd method
Clean up the temporary file.
delete(oFile);