Computational Imaging: Ptychography

May 11, 2016 Christina Mayer

 

Schematic illustration of how ptychography works. A sample is scanned using a coherent beam and the resulting diffraction image is observed. All the images are then merged and appropriately calculated to reconstruct the refractive properties of the phase objects.
Computational Imaging: Ptychographie
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Light interacting with matter forms the physical basis for most microscopic imaging processes. Thus it should come as no surprise that transparent objects (phase objects) – i.e. objects which only interact to a minimum degree with light – pose a quandary when creating an image. Making pure phase objects visible is not a new problem, and the search for better and innovative solutions continues.

Ptychography is one new approach from the field of computational imaging. In ptychography, a sample is illuminated using a coherent beam (e.g. a laser) and the diffraction image is observed at a large object distance. The beam is scanned over the sample with a large overlap of the illuminated area. To the naked eye, this single image is a completely useless diffraction image which looks like coherent noise (speckle). Thus the algorithmic evaluation of the data is essential – as this decodes the information contained in the diffraction patterns.

The unknown phase, i.e. the refractive properties of the object, is determined using the observed intensities of the speckle pattern. With modern enhancements, the exact illumination properties of the light source and the 3D structure of the object can also be determined using suitable physical modeling of this imaging process.

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Lars Omlor and Ivo Ihrke

References:

Atcheson, B., Ihrke, I., Heidrich, W., Tevs, A., Bradley, D., Magnor, M., & Seidel, H. P. (2008, December). Time-resolved 3d capture of non-stationary gas flows. In ACM transactions on graphics (TOG) (Vol. 27, No. 5, p. 132). ACM.

M. L. Faulkner and J. M. Rodenburg. Movable aperture lensless transmission microscopy: A novel phase retrieval algorithm. Phys. Rev. Lett., 93:023903, 2004.

Levoy, M., & Hanrahan, P. (1996, August). Light field rendering. In Proceedings of the 23rd annual conference on Computer graphics and interactive techniques (pp. 31-42). ACM.

Levoy, M., Ng, R., Adams, A., Footer, M., & Horowitz, M. (2006). Light field microscopy. ACM Transactions on Graphics (TOG), 25(3), 924-934.

Mignard-Debise, L., & Ihrke, I. (2015, October). Light-field Microscopy with a Consumer Light-field Camera. In 3D Vision (3DV), 2015 International Conference on (pp. 335-343). IEEE.

Tian, J. Wang, and L. Waller, "3D differential phase-contrast microscopy with computational illumination using an LED array," Optics Letters, vol. 39, no. 5, pp. 1326--1329, March 2014.

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