• 한국정보디스플레이학회:학술대회논문집
• /
• 2008.10a
• /
• pp.1131-1134
• /
• 2008

In this invited paper, numerical reconstruction and pattern recognition using integral imaging are overviewed. The computational integral imaging method reconstructs three-dimensional information at arbitrary depth-levels. Photon-counting nonlinear matched filtering combined with the computational reconstruction provides promising results for the application of low-light level recognition.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2008.10a
• /
• pp.726-729
• /
• 2008

In this paper, we present an interference problem among elemental images in computational integral imaging reconstruction. To overcome the interference problem, we propose a method to calculate a minimum magnification factor and the preliminary experiments are performed.

• ETRI Journal
• /
• v.28 no.4
• /
• pp.521-524
• /
• 2006

In this letter, we propose a novel computational integral imaging reconstruction technique based on a lenslet array model. The proposed technique provides improvement of viewing images by extracting multiple pixels from elemental images according to ray tracing based on the lenslet array model. To show the feasibility of the proposed technique, we analyze it according to ray optics and present the experimental results.

• Proceedings of the Optical Society of Korea Conference
• /
• 2007.07a
• /
• pp.257-258
• /
• 2007

For objective evaluation of computational integral imaging reconstruction (CIIR) schemes, a framework with the computational pickup and the CIIR process using Gaussian images is presented and characteristics of CIIR along the distance between lenslet array and objects are investigated.

• ETRI Journal
• /
• v.27 no.6
• /
• pp.708-712
• /
• 2005

We propose a computational reconstruction technique in large-depth integral imaging where the elemental images have information of three-dimensional objects through real and virtual image fields. In the proposed technique, we reconstruct full volume information from the elemental images through both real and virtual image fields. Here, we use uniform mappings of elemental images with the size of the lenslet regardless of the distance between the lenslet array and reconstruction image plane. To show the feasibility of the proposed reconstruction technique, we perform preliminary experiments and present experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.12
• /
• pp.2363-2369
• /
• 2016

In this paper, we propose three-dimensional (3D) quick-response (QR) code generation technique using passive 3D integral imaging and computational integral imaging reconstruction technique. In our proposed method, we divide 2D QR code into 4 planes with different reconstruction depths and then we generate 3D QR code using synthetic aperture integral imaging and computational reconstruction. In this 3D QR code generation process, we use integral imaging which is one of 3D imaging technologies. Finally, 3D QR code can be scanned by reconstructing and merging 3D QR codes at 4 different planes with computational reconstruction. Therefore, the security level for QR code scanning may be enhanced when QR code is scanned. To show that our proposed method can improve the security level for QR code scanning, in this paper, we carry out the optical experiments and computational reconstruction. In addition, we show that 3D QR code can be scanned when reconstruction depths are known.

• Journal of the Optical Society of Korea
• /
• v.12 no.3
• /
• pp.131-135
• /
• 2008

Computational integral imaging(CII) has the advantage of generating the volumetric information of the 3D scene without optical devices. However, the reconstruction process of CII requires increasingly larger sizes of reconstructed images and then the computational cost increases as the distance between the lenslet array and the reconstructed output plane increases. In this paper, to overcome this problem, we propose a novel CII method using a depth conversion technique. The proposed method can move a far 3D object near the lenslet array and reduce the computational cost dramatically. To show the usefulness of the proposed method, we carry out the preliminary experiment and its results are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.6
• /
• pp.2497-2517
• /
• 2020

For compressed sensing (CS) applications, it is significant to construct deterministic measurement matrices with good practical features, including good sensing performance, low memory cost, low computational complexity and easy hardware implementation. In this paper, a deterministic construction method of bipolar measurement matrices is presented based on binary sequence family (BSF). This method is of interest to be applied for sparse signal restore and image block CS. Coherence is an important tool to describe and compare the performance of various sensing matrices. Lower coherence implies higher reconstruction accuracy. The coherence of proposed measurement matrices is analyzed and derived to be smaller than the corresponding Gaussian and Bernoulli random matrices. Simulation experiments show that the proposed matrices outperform the corresponding Gaussian, Bernoulli, binary and chaotic bipolar matrices in reconstruction accuracy. Meanwhile, the proposed matrices can reduce the reconstruction time compared with their Gaussian counterpart. Moreover, the proposed matrices are very efficient for sensing performance, memory, complexity and hardware realization, which is beneficial to practical CS.

• Journal of the Optical Society of Korea
• /
• v.12 no.2
• /
• pp.88-92
• /
• 2008

This paper discusses a photon-counting linear discriminant analysis (LDA) with computational integral imaging (II). The computational II method reconstructs three-dimensional (3D) objects on the reconstruction planes located at arbitrary depth-levels. A maximum likelihood estimation (MLE) can be used to estimate the Poisson parameters of photon counts in the reconstruction space. The photon-counting LDA combined with the computational II method is developed in order to classify partially occluded objects with photon-limited images. Unknown targets are classified with the estimated Poisson parameters while reconstructed irradiance images are trained. It is shown that a low number of photons are sufficient to classify occluded objects with the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.10
• /
• pp.1944-1949
• /
• 2007

In this paper, a new plane-based computational reconstruction technique for three-dimensional (3D) objects in 3D internal imaging based on a lens model is proposed. For the proposed technique, computational experiments have been carried out for various test images. Resolution of the reconstructed images is analyzed and compared with that obtained by the conventional technique. From experiments, it is shown that the resolution of a 3-D reconstructed image was improved by using the proposed technique.