Method and system for hyperspectral light field imaging
First Claim
1. A method of generating hyperspectral data-cubes based on a plurality of hyperspectral light field (H-LF) images, wherein each H-LF image comprises a different view and a different spectral band, the method comprising:
- calculating a magnitude histogram, a direction histogram, and an overlapping histogram of oriented gradient for a plurality of pixels, wherein a bin in the overlapping histogram of oriented gradient comprises overlapping ranges of directions;
developing a spectral-invariant feature descriptor by combining the magnitude histogram, the direction histogram, and the overlapping histogram of oriented gradient;
obtaining a correspondence cost of the H-LF images based on the spectral-invariable feature descriptor;
performing H-LF stereo matching on the H-LF images to obtain a disparity map of a reference view; and
generating hyperspectral data-cubes by using the disparity map of the reference view.
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Abstract
A method for generating hyperspectral data-cubes based on a plurality of hyperspectral light field (H-LF) images is disclosed. Each H-LF image may have a different view and a different spectral band. The method may include calculating a magnitude histogram, a direction histogram, and an overlapping histogram of oriented gradient for a plurality of pixels; developing a spectral-invariant feature descriptor by combining the magnitude histogram, the direction histogram, and the overlapping histogram of oriented gradient; obtaining a correspondence cost of the H-LF images based on the spectral-invariable feature descriptor; performing H-LF stereo matching on the H-LF images to obtain a disparity map of a reference view; and generating hyperspectral data-cubes by using the disparity map of the reference view. A bin in the overlapping histogram of oriented gradient may comprise overlapping ranges of directions.
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Citations
23 Claims
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1. A method of generating hyperspectral data-cubes based on a plurality of hyperspectral light field (H-LF) images, wherein each H-LF image comprises a different view and a different spectral band, the method comprising:
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calculating a magnitude histogram, a direction histogram, and an overlapping histogram of oriented gradient for a plurality of pixels, wherein a bin in the overlapping histogram of oriented gradient comprises overlapping ranges of directions; developing a spectral-invariant feature descriptor by combining the magnitude histogram, the direction histogram, and the overlapping histogram of oriented gradient; obtaining a correspondence cost of the H-LF images based on the spectral-invariable feature descriptor; performing H-LF stereo matching on the H-LF images to obtain a disparity map of a reference view; and generating hyperspectral data-cubes by using the disparity map of the reference view. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method of generating hyperspectral data-cubes based on a plurality of hyperspectral light field (H-LF) images, wherein each H-LF image comprises a different view and a different spectral band, the method comprising:
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obtaining an estimated spectra by synthesizing RGB color values from the H-LF images and mapping the RGB color values to a spectral band; obtaining a defocus cost of the H-LF images based on a comparison between estimated spectra and captured spectra of the H-LF images; performing H-LF stereo matching on the H-LF images to obtain a disparity map of a reference view; and generating hyperspectral data-cubes by using the disparity map of the reference view. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A hyperspectral light field imaging (HLFI) system for capturing hyperspectral light field (H-LF) images to generate hyperspectral data-cubes, the system comprising:
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a plurality of multi-view hyperspectral data terminals configured to capture a plurality of H-LF images, wherein each H-LF image comprises a different view and a different spectral band; and a data processing unit configured to; calculate a magnitude histogram, a direction histogram, and an overlapping histogram of oriented gradient for a plurality of pixels, wherein a bin in the overlapping histogram of oriented gradient comprises overlapping ranges of directions; develop a spectral-invariant feature descriptor by combining the magnitude histogram, the direction histogram, and the overlapping histogram of oriented gradient; obtain a correspondence cost of the H-LF images based on the spectral-invariable feature descriptor; perform H-LF stereo matching on the H-LF images to obtain a disparity map of a reference view; and generate hyperspectral data-cubes by using the disparity map of the reference view. - View Dependent Claims (22, 23)
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Specification