RESUMO
In lens-based display systems, lens aberrations and depth of field (DoF) limitation often lead to blurring and distortion of reconstructed images; Meanwhile, expanding the display DoF will face a trade-off between horizontal resolution and axial resolution, restricting the achievement of high-resolution and large DoF three-dimensional (3D) displays. To overcome these constraints and enhance the DoF and resolution of reconstructed scenes, we propose a DoF expansion method based on diffractive optical element (DOE) optimization and image pre-correction through a convolutional neural network (CNN). This method applies DOE instead of the conventional lens and optimizes DOE phase distribution using the Adam algorithm, achieving depth-invariant and concentrated point spread function (PSF) distribution throughout the entire DoF range; Simultaneously, we utilize a CNN to pre-correct the original images and compensate for the image quality reduction introduced by the DOE. The proposed method is applied to a practical integral imaging system, we effectively extend the DoF of the DOE to 400 mm, leading to a high-resolution 3D display in multiple depth planes. To validate the effectiveness and practicality of the proposed method, we conduct numerical simulations and optical experiments.
RESUMO
In this paper, we propose a convolutional symmetric compressed look-up-table (CSC-LUT) method to accelerate computer-generated hologram (CGH) computation based on the Fresnel diffraction theory and LUT. The proposed method can achieve one-time high-quality fast generation of color holograms by utilizing dynamic convolution operation, which is divided three processes. Firstly, the pre-calculated data of maximum horizontal modulation factor is compressed in 1D array by coordinate symmetry. Then, the test object is resampled to satisfy convolutional translation invariance. Finally, the dynamic convolution operation is used to simplify CGH computation process rather than the point-by-point computation. Numerical simulation and optical experimental results show that our proposed method can achieve faster computation speed, higher reconstruction quality and wider application compared to conventional SC-LUT method. The further optimization method for parallel acceleration on the GPU framework can achieve real-time (>24fps) color holographic display corresponding to three perspectives of a 3D scene.
RESUMO
The spatial frequency of the reconstructed image of planar computer-generated hologram(CGH) is limited by the sampling interval and the lack of thickness. To break through this limitation of planar CGH, we propose a new computer-generated volume hologram(CGVH) for full-color dynamic holographic three-dimensional(3D) display, and an iteration-free layered CGVH generation method. The proposed CGVH is equivalent to a volume hologram sampled discretely in three directions. The generation method employs the layered angular spectral diffraction to calculate the light field in the layered CGVH, and then encodes it into a CGVH. Numerical simulation results show that the CGVH can accurately reconstruct full-color 3D objects, where better imaging quality, more concentrated diffraction energy, denser reconstructed spatial frequency information, and larger viewing angle are achieved. The proposed CGVH is expected to be applied to realize dynamic modulation, wavelength multiplexing, and angle multiplexing in various optical fields in the future.
RESUMO
One of the biggest challenges for large size three-dimensional (3D) holographic display based on the computer-generated hologram (CGH) is the trade-off between computation time and reconstruction quality, which has limited real-time synthesis of high-quality holographic image. In this paper, we propose a superpixel-based sub-hologram (SBS) method to reduce the computation time without sacrificing the quality of the reconstructed image. The superpixel-based sub-hologram method divides the target scene into a collection of superpixels. The superpixels are composed of adjacent object points. The region of the superpixel-based sub-hologram corresponding to each superpixel is determined by an approximation method. Since the size and the complexity of the diffraction regions are reduced, the hologram generation time is decreased significantly. The computation time has found to be reduced by 94.89% compared with the conventional sub-hologram method. It is shown that the proposed method implemented on the graphics processing unit (GPU) framework can achieve real-time (> 24 fps) color three-dimensional holographic display with a display size of 155.52 mm × 276.48 mm.
