Method and apparatus for generating computer-generated hologram

1. A method of generating a computer-generated hologram (CGH), the method comprising:

obtaining complex data including amplitude data of object data and phase data of the object data corresponding to a spatial light modulator (SLM) plane by propagating the object data from an image plane to the SLM plane;

encoding the complex data into encoded amplitude data; and

generating a CGH based on the object data including the encoded amplitude data,

wherein the obtaining of the complex data further comprises propagating the object data and obtaining the complex data based on a neural network.

2. The method of claim 1 , wherein the method further comprises, based on a plurality of image planes being set, obtaining and encoding the complex data for each of the plurality of image planes, and

wherein the generating of the CGH further comprises generating the CGH based on all of the object data including the encoded amplitude data corresponding to each of the plurality of image planes.

3. The method of claim 1 , wherein the SLM comprises an amplitude SLM, and

wherein the method further comprises outputting the generated CGH through the amplitude SLM.

4. A method of generating a computer-generated hologram (CGH), the method comprising:

obtaining complex data including amplitude data of object data and phase data of the object data corresponding to a spatial light modulator (SLM) plane by propagating the object data from an image plane to the SLM plane;

encoding the complex data into encoded amplitude data;

generating a CGH based on the object data including the encoded amplitude data, and

assigning phase data to the object data corresponding to the image plane based on a neural network.

5. The method of claim 4 , wherein the assigning of the phase data further comprises, based on the generated CGH being output through the SLM, assigning phase data based on a frequency of light, a distance between an observer and the SLM plane, and a size of an eye lens of the observer such that all light emitted from the SLM passes through the eye lens of the observer.

6. A method of generating a computer-generated hologram (CGH), the method comprising:

obtaining complex data including amplitude data of object data and phase data of the object data corresponding to a spatial light modulator (SLM) plane by propagating the object data from an image plane to the SLM plane;

encoding the complex data into encoded amplitude data based on a neural network; and

generating a CGH based on the object data including the encoded amplitude data.

7. The method of claim 6 , wherein the encoding further comprises:

inputting the complex data to the neural network;

inputting reverse output data from the neural network to the neural network in a reverse direction; and

obtaining a difference between the complex data and the reverse data output by the neural network with respect to the output data.

8. The method of claim 7 , wherein the encoding further comprises controlling the neural network to perform an operation with respect to the complex data to minimize the difference.

9. The method of claim 8 , wherein the encoding further comprises:

repeating the inputting the complex data to the neural network, the inputting reverse output data from the neural network, and the obtaining the difference until the difference is less than or equal to a preset size,

wherein a finally generated output data corresponds to the encoded amplitude data.

10. A computer-generated hologram (CGH) generating apparatus comprising:

a non-transitory memory configured to store at least one program; and

a processor configured to generate a CGH by executing the at least one program,

wherein the processor is further configured to:

obtain complex data including amplitude data of object and phase data of the object data corresponding to a spatial light modulator (SLM) plane by propagating object data from an image plane to the SLM plane,

encode the complex data into encoded amplitude data, and

generate the CGH based on the object data including the encoded amplitude data, and

wherein the processor is further configured to propagate the object data and obtain the complex data based on a neural network.

11. The CGH generating apparatus of claim 10 , wherein the processor is further configured to, based on the generated CGH being output through the SLM, assign the phase data based on a frequency of light, a distance between an observer and the SLM plane, and a size of an eye lens of the observer such that all light emitted from the SLM passes through the eye lens of the observer.

12. The CGH generating apparatus of claim 10 , wherein, based on a plurality of image planes being set, the processor is further configured to:

perform a process of obtaining and encoding the complex data for each of the plurality of image planes; and

generate the CGH based on all of the object data including the encoded amplitude data corresponding to each of the image planes.

13. The CGH generating apparatus of claim 10 , wherein the SLM comprises an amplitude SLM, and

wherein the processor is further configured to output the generated CGH through the amplitude SLM.

14. A computer-generated hologram (CGH) generating apparatus comprising:

a non-transitory memory configured to store at least one program; and

a processor configured to generate a CGH by executing the at least one program,

wherein the processor is further configured to:

obtain complex data including amplitude data of object and phase data of the object data corresponding to a spatial light modulator (SLM) plane by propagating object data from an image plane to the SLM plane,

encode the complex data into encoded amplitude data,

generate the CGH based on the object data including the encoded amplitude data, and

assign phase data to the object data corresponding to the image plane based on a deep neural network.

15. A computer-generated hologram (CGH) generating apparatus comprising:

a non-transitory memory configured to store at least one program; and

a processor configured to generate a CGH by executing the at least one program,

wherein the processor is further configured to:

obtain complex data including amplitude data of object and phase data of the object data corresponding to a spatial light modulator (SLM) plane by propagating object data from an image plane to the SLM plane,

encode the complex data into encoded amplitude data based on a neural network, and

generate the CGH based on the object data including the encoded amplitude.

16. The CGH generating apparatus of claim 15 , wherein the processor is further configured to:

input the complex data to the neural network;

input reverse output data from the neural network to the neural network in a reverse direction; and

obtain a difference between the reverse data output through the neural network and the complex data with respect to the output data.

17. The CGH generating apparatus of claim 16 , wherein the processor is further configured to control the neural network to perform an operation with respect to the complex data to minimize the difference.

18. The CGH generating apparatus of claim 17 , wherein the processor is further configured to repeat the inputting the complex data to the neural network, the inputting reverse output data from the neural network, and the obtaining the difference until the difference is less than or equal to a preset size, and

wherein a finally generated output data corresponds to the encoded amplitude data.

19. A non-transitory computer-readable recording medium having recorded thereon a program for executing a method on a computer, the method comprising:

obtaining complex data including amplitude data of object data and phase data of the object data corresponding to a spatial light modulator (SLM) plane by propagating the object data from an image plane to the SLM plane;

encoding the complex data into encoded amplitude data; and

generating a CGH based on the object data including the encoded amplitude data,

wherein the obtaining of the complex data further comprises propagating the object data and obtaining the complex data based on a neural network.