US 11,733,648 B2
Deep computational holography
Alexey Supikov, Santa Clara, CA (US); Qiong Huang, San Jose, CA (US); Anders Grunnet-Jepsen, San Jose, CA (US); Paul Winer, Aptos, CA (US); Ronald T. Azuma, San Jose, CA (US); and Ofir Mulla, Petach Tikva (IL)
Assigned to Intel Corporation, Santa Clara, CA (US)
Filed by Intel Corporation, Santa Clara, CA (US)
Filed on Jul. 25, 2022, as Appl. No. 17/872,669.
Application 17/872,669 is a continuation of application No. 16/451,518, filed on Jun. 25, 2019, granted, now 11,435,695.
Prior Publication US 2022/0357704 A1, Nov. 10, 2022
Int. Cl. G03H 1/08 (2006.01); G03H 1/26 (2006.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06N 3/08 (2023.01); G06F 18/214 (2023.01); G06V 10/44 (2022.01); G06V 10/60 (2022.01)
CPC G03H 1/0808 (2013.01) [G03H 1/2645 (2013.01); G06F 18/214 (2023.01); G06N 3/08 (2013.01); G06V 10/454 (2022.01); G06V 10/60 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G03H 2001/266 (2013.01); G03H 2210/441 (2013.01); G03H 2210/46 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
a memory to store target holographic image data and multi-channel image data corresponding to the target holographic image data, the multi-channel image data having an amplitude component channel and a phase component channel; and
a processor coupled to the memory, the processor to:
apply a pre-trained deep neural network to the multi-channel image data to generate intermediate diffraction pattern image data corresponding to the target holographic image data; and
apply an iterative process using a propagation model to the intermediate diffraction pattern image data to generate final diffraction pattern image data, wherein the propagation model corresponds to a holographic imaging arrangement to generate a holographic image using diffraction pattern image data.