APPARATUS AND METHOD FOR SNAPSHOT SPECTRAL IMAGING

• US 20160313181A1
• Filed: 06/16/2014
• Published: 10/27/2016
• Est. Priority Date: 06/18/2013
• Status: Active Grant

• Current Assignee: Ramot at Tel Aviv University Limited (Tel Aviv University)
• Original Assignee: Ramot at Tel Aviv University Limited (Tel Aviv University)
• Inventors: MALINSKY, Roman, ZHELUDEV, Valery, GOLUB, Michael, AVERBUCH, Amir, NATHAN, Menachem
• Granted Patent: US 9,823,126 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01J 2003/2826 Multispectral imaging, e.g. filter imaging
• CPC Class Codes: G01J 3/0205 Optical elements not provided otherwise, e.g. optical manifolds, diffusers, windows
• CPC Class Codes: G01J 3/027 Control of working procedures of a spectrometer; Failure detection; Bandwidth calculation
• CPC Class Codes: G01J 3/2823 Imaging spectrometer
• CPC Class Codes: G01J 3/36 Investigating two or more bands of a spectrum by separate detectors

Abstract

Apparatus and method for obtaining a plurality of spectral images of a source object in a snapshot using comprising two-dimensional compressed sensing data cube reconstruction (2D CS-SCR) applied to a dispersed-diffused snapshot image. In some embodiments, the snapshot image is obtained through a RIP diffuser. In some embodiments, a randomizer is used to further randomized the dispersed-diffused snapshot image. The 2D CS-SCR includes applying a 2D framelet transform separately to arrays representing different wavebands of spectral cube data derived from the snapshot image. The application of the 2D framelet transform separately to the arrays representing the different wavebands includes application of direct and inverse 2D framelet transforms to the arrays. In some embodiments, the direct and inverse framelet transforms are included in a split Bregman iteration.

Claims

1. Apparatus for obtaining a plurality of spectral images of a source object in a snapshot, comprising:

a) an imaging section of a digital camera that includes a lens and a pixelated image sensor, the imaging section configured to obtain a diffused and dispersed (DD) snapshot image Y; and

b) a digital processor configured to perform two-dimensional compressed sensing spectral cube reconstruction (2D CS-SCR) from snapshot image Y, thereby providing images of the source object in a plurality of spectral bands.

2. The apparatus of claim 1, wherein the processor configuration includes a configuration to apply a 2D framelet transform separately to arrays representing different wavebands of spectral cube data derived from snapshot image Y.

3. The apparatus of claim 2, wherein the configuration to apply a 2D framelet transform separately to arrays representing different wavebands of spectral cube data includes a configuration to apply direct and inverse 2D framelet transforms to the arrays representing the different wavebands.

4. The apparatus of claim 3, wherein the direct and inverse framelet transforms are included in a split Bregman iteration.

5. The apparatus of claim 1, wherein further comprising a restricted isometry property (RIP) diffuser inserted in an optical path between the source object and the image sensor, the RIP diffuser designed to satisfy a RIP condition related to a sensing matrix A, wherein the processor configuration includes a configuration to transpose matrix A to a transposed matrix A^T, to apply A^T to Y to obtain a matrix A^T Y, to apply a 2D direct sparsifying transform D to matrix A^T Y to obtain a sparse version d of a reconstructed data cube X, to use an inverse transform Ψ

to obtain X from d, and to process X to obtain the images of the source object in the plurality of spectral bands.

6. The apparatus of claim 1, wherein the processor is included in the digital camera.

7. The apparatus of claim 1, further comprising a randomizer configured to randomize snapshot image Y to obtain a randomized image, wherein the processor is further configured to perform the 2D CS-SCR from the randomized image.

8. The apparatus of claim 5, wherein the RIP diffuser is the form of a random phase mask implemented as a 1D grid of random groove depth steps.

9. The apparatus of claim 8, wherein the grid of random groove steps includes a randomized saw-tooth structure.

10. The apparatus of claim 7, wherein the randomizer is implemented as a thin optical element positioned adjacent to, or at an image sensor plane.

11. The apparatus of claim 10, wherein the randomizer element includes a pixelated structure identical with the image sensor pixelated structure.

12. The apparatus of claim 11, wherein the randomizer pixelated structure includes a random structure of pixels varying in transparency from 0 to 100%.

13. The apparatus of claim 7, wherein the randomizer is implemented as a software module in the processor.

14. A method for obtaining a plurality of spectral images of a source object in a snapshot, comprising the steps of:

a) obtaining a diffused and dispersed (DD) snapshot image Y; and

b) performing a two-dimensional compressed sensing data cube reconstruction (2D CS-SCR) from snapshot image Y, thereby providing images of the source object in a plurality of spectral bands.

15. The method of claim 14, wherein the step of obtaining a DD snapshot image Y includes imaging the source object with an imaging section of a digital camera that includes a lens and a pixelated image sensor.

16. The method of claim 14, wherein the step of performing a 2D CS-SCR from snapshot image Y includes applying a 2D framelet transform separately to arrays representing different wavebands of a spectral cube data derived from snapshot image Y.

17. The method of claim 16, wherein the applying a 2D framelet transform separately to arrays representing different wavebands of spectral cube data includes applying direct and inverse 2D framelet transforms to arrays representing the different wavebands.

18. The method of claim 17, wherein the direct and inverse framelet transforms are included in a split Bregman iteration.

19. The method of claim 15, wherein the step of imaging further includes imaging the source object through a restricted isometry property (RIP) diffuser inserted in an optical path between the source object and the image sensor, wherein the RIP diffuser satisfies a RIP condition related to a sensing matrix A.

20. The method of claim 19, wherein the step of performing a 2D CS-SCR from snapshot image Y includes:

i. transposing sensing matrix A into a transposed matrix A^T,

ii. applying A^T to snapshot image Y to obtain a matrix A^T Y,

ii applying a 2D direct sparsifying transform D to matrix A^T Y to obtain a sparse version d of a reconstructed data cube X,

iv. using an inverse transform Ψ

to obtain X from d, and

v. processing X by a split Bregman iteration to obtain the images of the source object in the plurality of spectral bands.

21. The method of claim 14, further comprising the step of randomizing the DD image to obtain a randomized image, wherein the step of performing a 2D CS-SCR includes performing the 2D CS-SCR from the randomized image.

22. The method of claim 21, wherein the step of randomizing includes using a thin optical randomizer element inserted between the RIP diffuser and the image sensor.

23. The method of claim 21, wherein the step of performing the 2D CS-SCR from the randomized image includes applying a 2D framelet transform separately to arrays representing different wavebands of a spectral cube data derived from the randomized image.

24. The method of claim 21, wherein the step of randomizing includes randomizing using a software-implemented randomizer.