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1. WO2020117245 - COMPUTATIONAL RECONFIGURABLE IMAGING SPECTROMETER

Note: Text based on automatic Optical Character Recognition processes. Please use the PDF version for legal matters

[ EN ]

CLAIMS

1. A hyperspectral imaging system comprising:

a first dispersive element to disperse an image moving laterally with respect to an optical axis of the hyperspectral imaging system into N spectral components;

a coding mask, in optical communication with the first dispersive element, to encode the N spectral components with a predetermined code;

a second dispersive element, in optical communication with the coding mask, to recombine the N spectral components into an encoded image;

a detector array, in optical communication with the second dispersive element and having M³ N detector elements, to detect the encoded image, wherein M and N are positive integers; and

a processor, operably coupled to the detector array, to form a reconstructed version of the image from the encoded image,

wherein the image moves fast enough to cause motion blur in the reconstructed version of the image and the processor is configured to estimate the motion blur from the reconstructed version of the image based on the predetermined code.

2. The hyperspectral imaging system of claim 1, wherein the coding mask is a static coding mask and the predetermined code is at least one of a binary Walsh-Hadamard S-matrix code or a random binary code.

3. The hyperspectral imaging system of claim 1, wherein the detector array comprises an uncooled microbolometer array configured to detect long-wave infrared radiation.

4. The hyperspectral imaging system of claim 1, wherein MIN > 10.

5. The hyperspectral imaging system of claim 1, wherein MIN > 100.

6. The hyperspectral imaging system of claim 1, wherein the processor is configured to form the reconstructed version of the image from the encoded image with a coding gain of jM/2N.

7. The hyperspectral imaging system of claim 1, wherein the detector array is configured to acquire a sequence of encoded images as the image moves laterally with respect to the optical axis of the hyperspectral imaging system and the processor is configured to estimate a trajectory of the image with respect to the hyperspectral imaging system based on the sequence of encoded images.

8. The hyperspectral imaging system of claim 1, further comprising:

a first lens, in optical communication with the coding mask, to focus the N spectral components onto the coding mask; and

a second lens, in optical communication with the coding mask and the detector array, to relay the encoded image to the detector array.

9. A method of hyperspectral imaging system, the method comprising:

dispersing a laterally moving image into N spectral components;

focusing the N spectral components onto a coding mask patterned with a predetermined code;

encoding the N spectral components with the predetermined code;

recombining the N spectral components into a laterally moving encoded image;

detecting the laterally moving encoded image with a detector array having M³ N resolvable detector elements, wherein M and N are positive integers;

forming a reconstructed version of the laterally moving image from the laterally moving encoded image, wherein the laterally moving image moves fast enough to cause motion blur in the reconstructed version of the image; and

removing the motion blur from the reconstructed version of the image based on the predetermined code.

10. The method of claim 9, wherein encoding the N spectral components comprises illuminating a static coding mask with a binary Walsh-Hadamard S-matrix code with the N spectral components.

11. The method of claim 9, wherein forming the reconstructed version of the laterally moving image from the laterally moving encoded image yields a coding gain of J M/2N .

12. The method of claim 9, wherein the laterally moving encoded image is a first laterally moving encoded image, and further comprising:

detecting a second laterally moving encoded image with the detector array after the image has moved by at least one resolvable spot with respect to the detector array; and

estimating a trajectory of the laterally moving image based on the first laterally moving encoded image and the second laterally moving encoded image.

13. The method of claim 9, further comprising:

reconfiguring the coding mask to improve spatial resolution when reconstructing the laterally moving image from the laterally moving encoded image.

14. The method of claim 9, further comprising:

reconfiguring the coding mask to improve spectral resolution when reconstructing the laterally moving image from the laterally moving encoded image.

15. A method of hyperspectral imaging, the method comprising:

separating a moving image into N spectral components propagating orthogonal to a direction of motion of the moving image;

focusing the A spectral components onto at least M spatially resolvable elements in a binary static mask;

recombining the N spectral components to form an encoded moving image;

sampling at least spatially resolvable spots of the encoded moving image at a frame rate / to form a hyperspectral data cube;

forming a reconstruction of the moving image with a coding gain of yj M/2N based on the hyperspectral data cube; and

estimating a trajectory of the moving image based on at least a portion of the

hyperspectral data cube.

16. The method of claim 15, wherein sampling the at least spatially resolvable spots of the encoded moving image comprises detecting long-wave infrared light with an uncooled bolometer array.

17. The method of claim 15, wherein the binary static mask applies a predetermined code to data in the hyperspectral data cube represented by a measurement matrix f and forming the reconstruction of the moving image comprises estimating spectra of the moving image with a pseudoinverse f+ of the measurement matrix.

18. The method of claim 17, wherein estimating the spectra comprises minimizing a mean squared error (MSE) equal to (s2/M) Trace(p+ p)-1, where s2 represents a variance of measurement noise associated with sampling the at least M spatially resolvable spots of the encoded moving image.

19. The method of claim 15, further comprising:

resolving motion of the moving image during a frame integration period T = 1/f based on at least a portion of the hyperspectral data cube; and

compensating the motion of the moving image during the frame integration period T = 1/f in the reconstruction of the moving image.