• Journal of the Optical Society of Korea
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• v.15 no.4
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• pp.357-361
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• 2011

Photon-counting sensing is a widely used technique for low-light-level imaging applications. This paper proposes a distance information extraction method with photon-counting passive sensing under low-lightlevel conditions. The photo-counting passive sensing combined with integral imaging generates a photon-limited elemental image array. Maximum-likelihood estimation (MLE) is used to reconstruct the photon-limited image at certain depth levels. The distance information is extracted at the depth level that minimizes the sum of the standard deviation of the corresponding photo-events in the elemental image array. Experimental and simulation results confirm that the proposed method can extract the distance information of the object under low-light-level conditions.

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

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.1135-1137
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• 2008

In this paper, it is proposed that the integral imaging technique is applied to reconstruct 3D (three dimensional) objects with enhanced depth of field, computationally and optically. Lens array using birefringence material is adopted to obtain the reconstruction. The elemental images sets are picked up through common micro lens array and utilized to present 3D reconstruction images using adopted lens array.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.155-157
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• 2012

In this paper, we propose a nonlinear 3D image correlator using computational reconstruction of 3D images based on integral imaging. In the proposed method, the elemental images for reference 3D object and target 3D object are recorded through the lens array. The recorded elemental images are reconstructed as reference plane image and target plane images using the computational integral imaging reconstruction algorithm and the nonolinear correlation between them is performed for object recognition. To show the usefulness of the proposed method, the preliminary experiments are carried out and the experimental results are presented compared with the conventional results.

• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.208-214
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• 2014

In this paper, in order to solve the problems of a narrow viewing angle and the flip effect in a three-dimensional (3D) integral imaging display, we propose an improved system by using an eye tracking method based on the Kinect sensor. In the proposed method, we introduce two types of calibration processes. First process is to perform the calibration between two cameras within Kinect sensor to collect specific 3D information. Second process is to use a space calibration for the coordinate conversion between the Kinect sensor and the coordinate system of the display panel. Our calibration processes can provide the improved performance of estimation for 3D position of the observer's eyes and generate elemental images in real-time speed based on the estimated position. To show the usefulness of the proposed method, we implement an integral imaging display system using the eye tracking process based on our calibration processes and carry out the preliminary experiments by measuring the viewing angle and flipping effect for the reconstructed 3D images. The experimental results reveal that the proposed method extended the viewing angles and removed the flipping images compared with the conventional system.

• Journal of information and communication convergence engineering
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• v.14 no.1
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• pp.57-63
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• 2016

In generally, the resolution of reconstructed three-dimensional images can be seriously degraded by undesired occlusions in the integral imaging system, because the undesired information of the occlusion overlap the three-dimensional images to be reconstructed. To solve the problem of the undesired occlusion, we present an exemplar-based image restoration method in integral imaging system. In the proposed method, a minimum spanning tree-based stereo matching method is used to remove the region of undesired occlusions in each elemental image. After that, the removed occlusion region of each elemental images are re-established by using the exemplar-based image restoration method. For further improve the performance of the image restoration, the structure tensor is used to solve the filling error cause by discontinuous structures. Finally, the resolution enhanced three-dimensional images are reconstructed by using the restored elemental images. The preliminary experiments are presented to demonstrate the feasibility of the proposed method.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.548-556
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• 2016

Integral imaging is an auto-stereoscopic display method that can produce 3D image of a finite viewing window through an array of micro elemental lenses. Integral imaging requires the pickup part of each elemental images acquisition and display part of reconstruction of the images. The successful reconstructed image depends on various parameters such as distance between lens arrays and display device, focal length of lenses, and a number of the array. In this paper, we present reconstruction emulator for display of Integral imaging in order to adjust parameters for 3D contents reconstruction and to observe the result from different configuration. Especially, we provide the user interface for the emulator to control the distance easily. We have confirmed through various experiments that the emulator adjusted the distance and could check error in the process of creating elemental images.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.153-159
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• 2018

In this paper, we present a three-dimensional (3D) optical encryption technique for quick response (QR) code using computational synthesized integral imaging, computational volumetric reconstruction, and double random phase encryption. Two-dimensional (2D) QR code has many advantages, such as enormous storage capacity and high reading speed. However, it does not protect primary information. Therefore, we present 3D optical encryption of QR code using double random phase encryption (DRPE) and an integral imaging technique for security enhancement. We divide 2D QR code into four parts with different depths. Then, 2D elemental images for each part of 2D QR code are generated by computer synthesized integral imaging. Generated 2D elemental images are encrypted using DRPE, and our method increases the level of security. To validate our method, we report simulations of 3D optical encryption of QR code. In addition, we calculated the peak side-lobe ratio (PSR) for performance evaluation.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.388-394
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• 2014

In this paper, we propose a three-dimensional (3D) image correlator by use of computational integral imaging reconstruction based on the modified convolution property of periodic functions (CPPF) for recognition of partially occluded objects. In the proposed correlator, elemental images of the reference and target objects are picked up by a lenslet array, and subsequently are transformed to a sub-image array which contains different perspectives according to the viewing direction. The modified version of the CPPF is applied to the sub-images. This enables us to produce the plane sub-image arrays without the magnification and superimposition processes used in the conventional methods. With the modified CPPF and the sub-image arrays, we reconstruct the reference and target plane sub-image arrays according to the reconstruction plane. 3D object recognition is performed through cross-correlations between the reference and the target plane sub-image arrays. To show the feasibility of the proposed method, some preliminary experiments on the target objects are carried out and the results are presented. Experimental results reveal that the use of plane sub-image arrays enables us to improve the correlation performance, compared to the conventional method using the computational integral imaging reconstruction algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.1111-1116
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• 2009

In this paper, we discuss distortion-tolerant pattern recognition using computational integral imaging reconstruction. Three-dimensional object information is captured by the integral imaging pick-up process. The captured information is numerically reconstructed at arbitrary depth-levels by averaging the corresponding pixels. We apply Fisher linear discriminant analysis combined with principal component analysis to computationally reconstructed images for the distortion-tolerant recognition. Fisher linear discriminant analysis maximizes the discrimination capability between classes and principal component analysis reduces the dimensionality with the minimum mean squared errors between the original and the restored images. The presented methods provide the promising results for the classification of out-of-plane rotated objects.