Feasibility study for super-resolution 3D integral imaging using time-multiplexed compressive coding

Color image guided depth image reconstruction based on a total variation network

A representative method to improve a depth image is to use an aligned high-quality color image to guide the depth image by migrating the color details to the depth image. In the process of color-guided depth reconstruction, there often is a misalignment of the edge of the color image used to guide the depth image reconstruction and the depth discontinuity of the depth image. This makes the results suffer from texture copy artifacts and blurring depth discontinuities. In this paper, we use a total variation deep network founded on deep learning and high-resolution color images. The experimental result indicates that under the guidance of high-resolution colors, the depth image recovered is closest to the ground truth in the edge contour, the PSNR and FSIM index are suboptimal for 64×, and the contour and position information recovered from the reconstructed depth image can be retained in the very low-resolution depth image.

Integral imaging three-dimensional display system with anisotropic backlight for the elimination of voxel aliasing and separation

Compared with conventional scattered backlight systems, integral imaging (InIm) display system with collimated backlight can reduce the voxel size, but apparent voxel separation and severe graininess still exist in reconstructed 3D images. In this paper, an InIm 3D display system with anisotropic backlight control of sub-pixels was proposed to resolve both voxel aliasing and voxel separation simultaneously. It consists of an anisotropic backlight unit (ABU), a transmissive liquid crystal panel (LCP), and a lens array. The ABU with specific horizontal and vertical divergence angles was proposed and designed. Within the depth of field, the light rays emitted from sub-pixels are controlled precisely by the ABU to minimize the voxel size as well as stitch adjacent voxels seamlessly, thus improving the 3D image quality effectively. In the experiment, the prototype of our proposed ABU-type InIm system was developed, and the spatial frequency was nearly two times of conventional scattered backlight InIm system. Additionally, the proposed system eliminated the voxel separation which usually occurs in collimated backlight InIm system. As a result, voxels reconstructed by our proposed system were stitched in space without aliasing and separation, thereby greatly enhancing the 3D resolution and image quality.

Bandwidth-enhanced depth priority integral imaging using a band-limited diffusing illumination technique

The display bandwidth and display mechanism determine the performance of the three-dimensional (3D) display system. In this paper, a bandwidth-enhanced depth priority integral imaging (DPII) technique is proposed. Information transmission efficiency (ITE) defined as the output display bandwidth divided by the input display bandwidth is used to assess the II system. By analyzing the ITE, we find that only a part of the input display bandwidth is used efficiently to present the 3D image in the traditional DPII system. The DPII system sacrifices the ITE for depth enhancement. The low ITE that fundamentally limits the 3D performance of the DPII system is ascribed to the diffusing illumination mechanism of the display system. To enhance the 3D performance, a collimated illumination DPII system as a special case of band-limited diffusing illumination technique has been proposed and demonstrated first. The bandwidth and ITE of such a DPII system are increased. The depth of field (DOF) of the system is doubled. The resolution of the 3D image is increased to the level of the resolution priority II system without sacrificing the viewing angle. A more general case, band-limited illumination DPII system is also demonstrated. By modulating the divergence angle of the illumination system, the 3D image's resolution and DOF can be controlled. The bandwidth and ITE of the DPII system using band-limited illumination are also higher than that of the traditional DPII system. Experiments are presented to prove the bandwidth-enhanced mechanism of the DPII system.

Wavelet-based iterative perfect reconstruction in computational integral imaging

We propose a new computational integral imaging (CII) method via the iterative perfect reconstruction technique to improve the visual quality of reconstructed 3D scenes. As is well known, images reconstructed by CII suffer from artifacts and, as a result, degradation of visual quality. As solutions to this problem, the regularization and iterative back-projection (IBP)-based super-resolution (SR) reconstruction algorithms have been shown to be effective for high-visual-quality reconstruction. However, computation of the regularization algorithm is very expensive, and the IBP algorithm is very sensitive to noise in the deblurring process. To address these challenges, we propose an iterative perfect reconstruction algorithm that addresses the issues of low visual quality and noise sensitivity. Experimental results indicate that our proposed method outperforms the conventional SR reconstruction-based CII methods.