Computational volumetric reconstruction of integral imaging with improved depth resolution considering continuously non-uniform shifting pixels

In this paper, we propose a new computational volumetric reconstruction technique of three-dimensional (3D) integral imaging for depth resolution enhancement by using non-uniform and integer-valued shifting pixels. In a typical integral imaging system, 3D images can be recorded and visualized using a lenslet array. In previous studies, many computational reconstruction techniques such as computational volumetric reconstruction and pixel of elemental images rearrangement technique (PERT) have been reported. However, a computational volumetric reconstruction technique has low visual quality and depth resolution because low-resolution elemental images and uniformly distributed shifting pixels are used for reconstruction. Although PERT can enhanced the visual quality of the 3D images, the size of the reconstructed 3D images is different from the original scene. On the other hand, our proposed method uses non-uniformly distributed shifting pixels for reconstruction instead of uniformly distributed shifting pixels. Therefore, the visual quality and depth resolution may be enhanced. Finally, our experimental results show the improvement of depth resolution and visual quality of the reconstructed 3D images

Performance analysis on color image mosaicing techniques on FPGA

Today, the surveillance systems and other monitoring systems are considering the capturing of image sequences in a single frame. The captured images can be combined to get the mosaiced image or combined image sequence. But the captured image may have quality issues like brightness issue, alignment issue (correlation issue), resolution issue, manual image registration issue etc. The existing technique like cross correlation can offer better image mosaicing but faces brightness issue in mosaicing. Thus, this paper introduces two different methods for mosaicing i.e., (a) Sliding Window Module (SWM) based Color Image Mosaicing (CIM) and (b) Discrete Cosine Transform (DCT) based CIM on Field Programmable Gate Array (FPGA). The SWM based CIM adopted for corner detection of two images and perform the automatic image registration while DCT based CIM aligns both the local as well as global alignment of images by using phase correlation approach. Finally, these two methods performances are analyzed by comparing with parameters like PSNR, MSE, device utilization and execution time. From the analysis it is concluded that the DCT based CIM can offers significant results than SWM based CIM

Polarimetric 3D integral imaging in photon-starved conditions

We develop a method for obtaining 3D polarimetric integral images from elemental images recorded in low light illumination conditions. Since photon-counting images are very sparse, calculation of the Stokes parameters and the degree of polarization should be handled carefully. In our approach, polarimetric 3D integral images are generated using the Maximum Likelihood Estimation and subsequently reconstructed by means of a Total Variation Denoising filter. In this way, polarimetric results are comparable to those obtained in conventional illumination conditions. We also show that polarimetric information retrieved from photon starved images can be used in 3D object recognition problems. To the best of our knowledge, this is the first report on 3D polarimetric photon counting integral imaging

Analysis of the depth of field of integral imaging displays based on wave optics

In this paper, we analyze the depth of field (DOF) of integral imaging displays based on wave optics. With considering the diffraction effect, we analyze the intensity distribution of light with multiple microlenses and derive a DOF calculation formula for integral imaging display system. We study the variations of DOF values with different system parameters. Experimental results are provided to verify the accuracy of the theoretical analysis. The analyses and experimental results presented in this paper could be beneficial for better understanding and designing of integral imaging displays

Estimation of the degree of polarization in low-light 3D integral imaging

The calculation of the Stokes Parameters and the Degree of Polarization in 3D integral images requires a careful manipulation of the polarimetric elemental images. This fact is particularly important if the scenes are taken in low-light conditions. In this paper, we show that the Degree of Polarization can be effectively estimated even when elemental images are recorded with few photons. The original idea was communicated in [A. Carnicer and B. Javidi, 'Polarimetric 3D integral imaging in photon-starved conditions,' Opt. Express 23, 6408-6417 (2015)]. First, we use the Maximum Likelihood Estimation approach for generating the 3D integral image. Nevertheless, this method produces very noisy images and thus, the degree of polarization cannot be calculated. We suggest using a Total Variation Denoising filter as a way to improve the quality of the generated 3D images. As a result, noise is suppressed but high frequency information is preserved. Finally, the degree of polarization is obtained successfully

Three-Dimensional Photon Counting Integral Imaging Reconstruction using Merging Reconstruction Method

In this paper, we propose a new three-dimensional (3D) photon counting integral imaging reconstruction method using elemental image merging process for the effective use of the extracted photons under severely photon starved conditions. In previous methods, the photons are extracted from elemental images using Poisson random process and 3D images are reconstructed by Maximum Likelihood Estimation (MLE). However, 3D integral imaging with photon counting do not use the photons effectively in reconstruction. Thus, it may not visualize 3D objects in severely low light level conditions. In addition, it may not generate high-quality reconstructed 3D images when the number of the recorded elemental images is insufficient. Therefore, to solve these problems, we propose a new 3D reconstruction method for photon counting integral imaging, which can generate high-quality 3D images without photon loss in the reconstruction process. To prove our method, we carry out the simulation experiments.2nd International Conference on Artificial Intelligence in Information and Communication (ICAIIC 2020), February 19-21, 2020, Fukuoka, Japa

3D Visualization of Objects under scattering media conditions using Integral Imaging

In this paper, we propose a new three-dimensional (3D) reconstruction technique in scattering media using integral imaging. In conventional integral imaging, it can visualize 3D images well when high-resolution elemental images are used. However, when low-resolution images are used, the visual quality of the 3D images is reduced. In addition, it is difficult to recognize the objects under scattering media conditions. Therefore, to visualize 3D images in scattering media, we create a mask filter in frequency domain to remove the scattering media. In addition, we calculate the density of the scattered media to adjust the contrast and histogram equalization automatically. To prove our method, we implemented optical experiments.The 10th International Conference on Information and Communication Technology Convergence (ICTC 2019), 16-18 October 2019, Jeju Island, Kore

Scatter denoising technique using Fourier domain filtering and integral imaging

Scatter denoising is a challenging project for removing noise under scattered media conditions such as fog and turbid water. In the previous studies, blurring caused by scattering media particles in fog or turbid water was solved by low-pass filtering or by removing the estimated scattering media and then amplifying the brightness with the photon-counting algorithm. However, these methods lose the accurate color information of the object by low-frequency filtering or using the probability-based photon-counting algorithm. Moreover, it is difficult to obtain shape information of an object under heavy turbidity. To solve this problem, we propose a new algorithm of scatter removal by combining Fourier domain filtering and integral imaging. To prove the proposed method, we carry out numerical analysis of experimental results by previous method and our proposed method.13th International Conference on ITC Convergence (ICTC2021), October 20-22, 2021, Jeju, Kore

Free-view pixels of elemental image rearrangement technique (FPERT)

In this paper, we propose a new free-view three-dimensional (3D) computational reconstruction of integral imaging to improve the visual quality of reconstructed 3D images when low-resolution elemental images are used. In a conventional free-view reconstruction, the visual quality of the reconstructed 3D images is insufficient to provide 3D information to applications because of the shift and sum process. In addition, its processing speed is slow. To solve these problems, our proposed method uses a pixel rearrangement technique (PERT) with locally selective elemental images. In general, PERT can reconstruct 3D images with a high visual quality at a fast processing speed. However, PERT cannot provide a free-view reconstruction. Therefore, using our proposed method, free-view reconstructed 3D images with high visual qualities can be generated when low-resolution elemental images are used. To show the feasibility of our proposed method, we applied it to optical experiments