Method and apparatus for modulating depth of hologram and holographic display using the same

Patent metadata

Field	Value
Publication number	US-12130589-B2
Application number	US-202217885258-A
Country	US
Kind code	B2
Filing date	Aug 10, 2022
Priority date	Jan 21, 2022
Publication date	Oct 29, 2024
Grant date	Oct 29, 2024

Abstract

A method of modulating a depth of a hologram, the method includes: obtaining hologram data; determining a scale factor based on a hardware specification of a holographic display to display a three-dimensional (3D) hologram image in a space by using the hologram data; and modulating depth information of the hologram data based on the scale factor.

First claim

What is claimed is:

1. A method of modulating a depth of a hologram, the method comprising:
obtaining hologram data;
determining a scale factor based on an actual hardware specification of a holographic display to display a three-dimensional (3D) hologram image in a space by using the hologram data; and
modulating depth information of the hologram data based on the scale factor,
wherein the modulating of the depth information of the hologram data comprises modulating the depth information of the hologram data by using a neural network trained to correct depth distortion due to a difference between an assumed hardware specification assumed when generating the hologram data and the actual hardware specification of the holographic display.

2. The method of claim 1 , wherein the modulating of the depth information of the hologram data further comprises:
selecting, among a plurality of pre-trained neural networks, the neural network corresponding to the scale factor; and
obtaining modulated hologram data by inputting the hologram data to the selected neural network.

3. The method of claim 1 , wherein the modulating of the depth information of the hologram data further comprises obtaining modulated hologram data by using a pre-trained neural network having both the scale factor and the hologram data as inputs.

4. The method of claim 1 , further comprising training the neural network,
wherein the training of the neural network comprises:
generating input hologram data based on a red-green-blue (RGB) image and a depth map;
obtaining output hologram data by inputting the input hologram data to the neural network;
generating focal stack images by propagating the output hologram to certain depths; and
training the neural network based on a loss function representing a difference between the focal stack images and reference focal images.

5. The method of claim 4 , wherein the reference focal images correspond to target hologram data generated by directly reflecting the scale factor to the RGB image and the depth map.

6. The method of claim 4 , wherein the neural network is trained to output target hologram data based on an input of the input hologram data without information about the RGB image and the depth map corresponding to the input hologram data.

7. The method of claim 4 , wherein the certain depths are variable based on the scale factor.

8. The method of claim 1 , wherein the determining of the scale factor comprises calculating the scale factor based on a ratio between a pixel pitch assumed when generating the hologram data and an actual pixel pitch of the holographic display.

9. The method of claim 1 , wherein the hologram data corresponds to hologram contents directly captured by a holographic camera or previously generated through computer-generated holography (CGH).

10. A hologram depth modulation apparatus comprising:
a memory storing one or more instructions; and
a processor configured to execute the one or more instructions to:
obtain hologram data,
determine a scale factor based on an actual hardware specification of a holographic display to display a three-dimensional (3D) hologram image in a space by using the hologram data, and
modulate depth information of the hologram data based on the scale factor,

wherein the processor is further configured to modulate the depth information of the hologram data by using a neural network trained to correct depth distortion due to a difference between an assumed hardware specification assumed when generating the hologram data and the actual hardware specification of the holographic display.

11. The hologram depth modulation apparatus of claim 10 , wherein the processor is further configured to select, among a plurality of pre-trained neural networks, the neural network corresponding to the scale factor, and obtain modulated hologram data by inputting the hologram data to the selected neural network.

12. The hologram depth modulation apparatus of claim 10 , wherein the processor is further configured to obtain modulated hologram data by using a pre-trained neural network having both the scale factor and the hologram data as inputs.

13. The hologram depth modulation apparatus of claim 10 , wherein the processor is further configured to:
generate input hologram data based on a red-green-blue (RGB) image and a depth map,
obtain output hologram data by inputting the input hologram data to the neural network,
generate focal stack images by propagating an output hologram to certain depths, and
train the neural network based on a loss function representing a difference between the focal stack images and reference focal images.

14. The hologram depth modulation apparatus of claim 13 , wherein the reference focal images correspond to target hologram data generated by directly reflecting the scale factor to the RGB image and the depth map.

15. The hologram depth modulation apparatus of claim 13 , wherein the neural network is trained to output target hologram data based on an input of the input hologram data without information about the RGB image and the depth map corresponding to the input hologram data.

16. The hologram depth modulation apparatus of claim 13 , wherein the certain depths are variable based on the scale factor.

17. The hologram depth modulation apparatus of claim 10 , wherein the processor is further configured to calculate the scale factor based on a ratio between a pixel pitch assumed when generating the hologram data and an actual pixel pitch of the holographic display.

18. A holographic display comprising:
at least one optical element;
a spatial light modulator (SLM) configured to modulate light incident from the at least one optical element;
a memory storing one or more instructions; and
at least one processor configured to execute the one or more instructions to:
obtain hologram data, determine a scale factor based on an actual hardware specification of a holographic display to display a three-dimensional (3D) hologram image in a space by using the hologram data, modulate depth information of the hologram data based on the scale factor, and play modulated hologram data by using the at least one optical element and the SLM

wherein the at least one processor is further configured to modulate the depth information of the hologram data by using a neural network trained to correct depth distortion due to a difference between an assumed hardware specification assumed when generating the hologram data and the actual hardware specification of the holographic display.

Assignees

• Samsung Electronics Co Ltd

Inventors

• Yu Hyeonseung
• Yang Daeho
• Lee Hongseok
• Seo Wontaek

Classifications

• G06T2207/20084

  Artificial neural networks [ANN] · CPC title

• G06T2207/20081

  Training; Learning · CPC title

• G06T2207/10024

  Color image · CPC title

• G03H2226/02

  Computing or processing means, e.g. digital signal processor [DSP] · CPC title

• G03H2225/30

  Modulation · CPC title