Fast Mapping of Double-Pixel Holograms using K-Nearest Neighbors

Ahmadi, Kavan; Maluenda, David; Carnicer, Artur

doi:10.1364/dh.2021.dw5e.7

Cited by 2 publications

(2 citation statements)

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“…For instance, to generate a 768 Â 1024 pixels CGH, and since four pixels at the SLM plane provide one holographic cell, there are (768 Â 1024)/4 = 196,608 holographic cells that should be mapped among all accessible complex values. In [40], we presented a method using the k-NN classifier, which is able to generate DPHs 80 times faster than the conventional calculation.…”

Section: Fast Generating Dphs Using K-nnmentioning

confidence: 99%

Beam Implementation with a Translucent Twisted-Nematic Liquid Crystal Display

Ahmadi¹

2023

Holography - Recent Advances and Applications

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This chapter describes an efficient approach to generating light beams with arbitrary intensity profile and phase distribution. Accordingly, a fast method is described to characterize liquid crystal displays based on the Mach-Zehnder interferometer and fringe analysis in the Fourier domain. Then, the double-pixel hologram Arrizón’s approach is reviewed. This approach is able to generate an on-axis computer-generated hologram into a low-resolution twisted-nematic liquid crystal for encoding arbitrary complex modulations. Furthermore, a fast algorithm to map holographic cells based on the k-nearest neighbor (k-NN) classifier is introduced in order to generate computer-generated holograms faster than the conventional calculation. Finally, two beam profiles are produced with the described approach and assessed at the entrance pupil and the depth of focus of a high-NA microscope objective.

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Section: Fast Generating Dphs Using K-nnmentioning

confidence: 99%

Beam Implementation with a Translucent Twisted-Nematic Liquid Crystal Display

Ahmadi¹

2023

Holography - Recent Advances and Applications

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“…(7 -8). This realvalued distribution is introduced in the optical system using a computer generated hologram displayed on a liquid crystal device [61,62], as described in the next section (see Fig. 2c).…”

Section: Encoding Proceduresmentioning

confidence: 99%