A Fast Hologram Calculation Method Based on Macular Region Optimized Sub-hologram Segmentation

Abstract

This invention proposes a fast hologram calculation method based on optimized sub-hologram segmentation of the macular region. The method includes the following three steps: First, the 3D object is segmented according to depth information to obtain 2D planes with different depth information, and the diffraction distance of each 2D plane is calculated. Second, an initial sub-hologram is generated for each 2D plane based on Fresnel diffraction theory. The initial sub-holograms are then optimized and segmented according to the viewing position, macular size, and diffraction distance of the 2D planes to obtain an effective sub-hologram for each 2D plane. Third, the effective sub-holograms corresponding to each 2D plane are superimposed to obtain the final 3D hologram. The 3D hologram is then loaded onto a spatial light modulator for optical reconstruction. When the spatial light modulator is illuminated by a light source, a reconstructed image of the 3D object is observed.

Description

I. Technical Field

[0001] This invention relates to holographic display technology, and more specifically, to a fast hologram calculation method based on optimized segmentation of sub-holograms in the macular region. II. Background Technology

[0002] Holographic 3D display technology records all wavefront information of a 3D object based on the principle of interference and reconstructs it based on the principle of diffraction, avoiding visual fatigue caused by convergence-accommodation conflict, making it one of the most ideal 3D display technologies. However, due to the massive amount of information in 3D objects, hologram calculation requires a significant amount of time, limiting the application of holographic 3D displays and hindering the further development of dynamic holographic displays. To improve the calculation speed of holograms, researchers proposed a novel lookup table method. This method discretizes 3D objects as independent point light sources and groups them according to depth. During the calculation process, only the central fringe pattern of each group needs to be pre-calculated and stored, thus significantly reducing the computation time required for generating holograms using the traditional lookup table method. Subsequently, researchers proposed a separate lookup table method, which reduces data storage and shortens the hologram calculation time by simplifying the mathematical expression of spherical waves. Other researchers have optimized the segmentation of holograms by analyzing the effective viewing area of ​​the reconstructed image, thereby reducing the computational load and improving the calculation speed. With the development of computer technology, more fast hologram generation methods based on different principles have been proposed, such as phase tracing, pixel-based methods, and hardware acceleration methods. However, the current hologram calculation speed is still insufficient to meet the requirements of real-time dynamic holographic displays. How to achieve fast hologram calculation remains a major concern in the field of holographic displays. III. Summary of the Invention

[0003] This invention proposes a fast hologram calculation method based on optimized segmentation of sub-holograms in the macular region. (See attached diagram) Figure 1 As shown, the method includes the following three steps: First, the 3D object is layered according to depth information to obtain 2D planes with different depth information, and the diffraction distance of each 2D plane is calculated; Second, an initial sub-hologram corresponding to each 2D plane is generated based on Fresnel diffraction theory, and the initial sub-hologram is optimized and segmented according to the viewing position, macula size, and diffraction distance of the 2D plane to obtain an effective sub-hologram for each 2D plane; Third, the effective sub-holograms corresponding to each 2D plane are superimposed to obtain the final 3D hologram. The 3D hologram is loaded onto a spatial light modulator for optical reconstruction. When the spatial light modulator is illuminated by a light source, the reconstructed image of the 3D object is seen. The method proposed in this invention analyzes the size of the effective sub-hologram corresponding to each 2D plane of the reconstructed image based on the macula size, thereby reducing the amount of computation and improving the calculation speed.

[0004] In step one, based on the depth information, the 3D object is divided into N 2D planes with different depth information, and the size of the nth 2D plane is denoted as M. n The diffraction distance is denoted as Z. n , where n = 1, 2, 3…N.

[0005] In step two, taking the nth layer 2D plane as an example, the principle of optimized segmentation analysis of the sub-hologram is as follows: Figure 2 As shown, A and B are the two endpoints of the nth 2D plane, K is any point on the 2D plane, and A', B', and K' are the reconstructed image points corresponding to points A, B, and K, respectively. According to the Fresnel diffraction principle, the viewing angle of the reconstructed image on the 2D plane is limited by the maximum diffraction angle θ of the spatial light modulator.

[0006]

[0007] Where λ is the wavelength of the light source used, and p is the pixel pitch of the spatial light modulator. (See attached image) Figure 2 As shown in (a), when the viewer is located at a distance L behind the spatial light modulator, region CD is the viewing area of ​​object point A during the reconstruction of the initial sub-hologram n, and region EF is the viewing area of ​​object point B during the reconstruction of the initial sub-hologram n. Therefore, region ED is the complete viewing area of ​​the nth layer 2D plane during the reconstruction of the initial sub-hologram n. Region OQ is the effective area of ​​the macula of the human eye, and within the complete viewing area ED, region OQ is significantly smaller than region ED. The viewer can only see the reconstructed image if and only if the reconstructed information enters the macula of the human eye. Therefore, the reconstructed information corresponding to regions other than the macula of the human eye is redundant information, affecting the calculation speed of the hologram.

[0008] The principle of optimizing the segmentation of the initial sub-hologram based on the size of the macular region in this invention is as follows: Figure 2 As shown in (b), S A S represents the effective sub-hologram size of object point A after optimized segmentation based on the macular region. B Let S be the effective sub-hologram size of object point B after optimized segmentation based on the macular region, and let S be the effective sub-hologram size of any object point K on the nth layer 2D plane after optimized segmentation based on the macular region. These values ​​are calculated based on geometric analysis.

[0009]

[0010] Where R is the size of the macular region OQ. Analysis shows that the effective sub-holograms after optimized segmentation based on the macular region have the same size, i.e., S. A =S B=S, and smaller than the size of the spatial light modulator. According to formula (2), the initial sub-hologram of each object point in the nth layer 2D plane is optimized and segmented to determine the region of the effective sub-hologram, and the effective sub-hologram of the nth layer 2D plane is obtained by superimposing the effective sub-holograms of adjacent object points.

[0011] In step three, the effective sub-holograms corresponding to different 2D planes are superimposed to obtain the final 3D hologram. During the holographic reconstruction process, the 3D hologram generated in step three is loaded onto a spatial light modulator. When the spatial light modulator is illuminated by coherent parallel light, a holographic 3D reconstructed image is generated. IV. Description of the attached drawings

[0012] Appendix Figure 1 This is a schematic diagram of a fast hologram calculation method based on optimized sub-hologram segmentation in the macular region according to the present invention.

[0013] Appendix Figure 2 This is a schematic diagram of a sub-hologram based on macular region optimization according to the present invention. (Attached) Figure 2 (a) is a schematic diagram of the reconstruction range based on the initial sub-hologram; Appendix Figure 2 (b) is a schematic diagram of optimizing the segmentation of the initial sub-hologram based on the macular region.

[0014] Appendix Figure 3 This is a comparison of the computation time of the fast hologram calculation method based on the optimized segmentation of sub-holograms in the macular region according to the present invention and the traditional novel lookup table method.

[0015] It should be understood that the above figures are only schematic and are not drawn to scale. V. Detailed Implementation Methods

[0016] The following detailed description of an embodiment of the fast hologram calculation method based on optimized sub-hologram segmentation of the macular region proposed in this invention further illustrates the invention. It is necessary to point out that the following embodiments are only used for further explanation of this invention and should not be construed as limiting the scope of protection of this invention. Any non-essential improvements and adjustments made to this invention by those skilled in the art based on the above description still fall within the scope of protection of this invention.

[0017] One embodiment of the present invention is as follows: In the hologram generation process, green light with a wavelength of 532nm is selected as the light source. The spatial light modulator used in the experiment is a reflective pure phase spatial light modulator with a pixel pitch of 6.4μm, a resolution of 1920×1080, and a phase modulation capability of 2π, and the pixel pitch of the hologram is set accordingly. Objects with resolutions of 300×300, 400×400, and 500×500 are selected as the recorded objects, the diffraction distance is set to 10cm, the distance between the observer and the spatial light modulator is set to 30cm, and the size of the human eye's macula is 0.55cm×0.55cm. The computer configuration used to calculate the 3D hologram is an 11th generation Gen Intel(R) Core(TM) i7-11700KF processor (3.60GHz), and the calculation software is Python 3.9.13. When using the conventional lookup table method, the sub-hologram resolution for each object point is equal to the resolution of the spatial light modulator, which is 1920×1080. In this case, the hologram generation times are 670s, 1173s, and 1847s, respectively. When using the method of this invention, the effective sub-hologram resolution for each object point is 430×430, and the 3D hologram generation times are 455s, 796s, and 1247s, respectively. A comparison of the calculation times is attached. Figure 3 As shown, compared with the traditional novel lookup table method, the method of the present invention significantly improves the hologram calculation speed.

Claims

1. A fast hologram calculation method based on macular area optimized segmentation of sub-holograms, characterized by, The method comprises the following three steps: first, layering the 3D object according to the depth information to obtain 2D planes with different depth information, and calculating the diffraction distance of each 2D plane; second, generating the initial sub-hologram corresponding to each 2D plane based on the Fresnel diffraction theory, and performing optimized segmentation analysis on the initial sub-hologram according to the viewing position, the size of the macula and the diffraction distance of the 2D plane to obtain the effective sub-hologram of each 2D plane; and third, superimposing the effective sub-hologram corresponding to each 2D plane to obtain the final 3D hologram. The size of the effective sub-hologram corresponding to each 2D plane of the reconstructed image is analyzed according to the size of the macula, so as to reduce the calculation amount. In step one, according to the depth information, the 3D object is divided into N 2D planes with different depth information, and the size of the nth 2D plane is recorded as M n , and the diffraction distance is recorded as Z n , where n = 1, 2, 3…N In step two, taking the nth 2D plane as an example, the principle of optimized segmentation analysis of the sub-hologram is that when the viewer is located at a position with a distance of L behind the spatial light modulator, the viewer can only watch the reconstructed image when the reconstructed information enters the macula of the human eye, and the reconstructed information corresponding to the area outside the macula of the human eye is redundant information, which affects the calculation speed of the hologram; the effective area of the macula of the human eye is smaller than the complete viewing area of the nth 2D plane when the initial sub-hologram is reconstructed, the size of the effective sub-hologram of any object point on the nth 2D plane after optimized segmentation based on the macula is denoted as S, and S is calculated according to geometric analysis as follows: wherein R is the size of the macula; for any object point, the size of the effective sub-hologram after optimized segmentation based on the macula is the same and smaller than the size of the spatial light modulator; the initial sub-hologram of each object point of the nth 2D plane is respectively optimized and segmented to determine the area of the effective sub-hologram, and the effective sub-hologram of the nth 2D plane is obtained by superimposing the effective sub-holograms of adjacent object points; and the effective sub-holograms corresponding to different layers of 2D planes are superimposed to obtain the final 3D hologram.

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