• 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.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.757-760
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• 2008

In this paper, an improved computational integral imaging reconstruction (CIIR) is proposed. The proposed method can highly enhance the viewing quality of reconstructed image. To show the feasibility of proposed method, some experiments are performed and the results are compared and discussed with those of the conventional method.

• Journal of the Optical Society of Korea
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• v.20 no.3
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• pp.363-367
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• 2016

In this paper, we present a resolution-enhanced computational integral imaging reconstruction method by using boundary folding mirrors. In the proposed method, to improve the resolution of the computationally reconstructed 3D images, the direct and reflected light information of the 3D objects through a lenslet array with boundary folding mirrors is recorded as a combined elemental image array. Then, the ray tracing method is employed to synthesize the regular elemental image array by using a combined elemental image array. From the experimental results, we can verify that the proposed method can improve the visual quality of the computationally reconstructed 3D images.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.730-733
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• 2008

In this paper, a novel CII method using a depth conversion technique is proposed. The proposed method can move a far 3D object near lenslet array and reduce the computation cost dramatically. To show the usefulness of the proposed method, we carry out the preliminary experiment and its results are presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1164-1170
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• 2011

In this paper, we propose accurate lattice extraction of elemental image array and pre-processing methods in computational integral imaging. Pre-processing methods remove distortions and noises of the image. Such distortions occurred in pickup systems are rotational errors. Distortions will degrade the resolution of reconstructed images. To overcome this problem, we propose our methods for extraction of elemental image array and pre-processing methods. Also, we describe that distortions affect the high quality reconstruction. Optical and computational experiments indicate that reconstructed images applied our methods is better than reconstructed images unapplied our methods.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.180-187
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• 2021

In this paper, we present a computational volumetric reconstruction method for three-dimensional (3D) photon counting imaging with enhanced visual quality when low-resolution elemental images are used under photon-starved conditions. In conventional photon counting imaging with low-resolution elemental images, it may be difficult to estimate the 3D scene correctly because of a lack of scene information. In addition, the reconstructed 3D images may be blurred because volumetric computational reconstruction has an averaging effect. In contrast, with our method, the pixels of the elemental image rearrangement technique and a Bayesian approach are used as the reconstruction and estimation methods, respectively. Therefore, our method can enhance the visual quality and estimation accuracy of the reconstructed 3D images because it does not have an averaging effect and uses prior information about the 3D scene. To validate our technique, we performed optical experiments and demonstrated the reconstruction results.

• 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.

• Journal of the Optical Society of Korea
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• v.19 no.3
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• pp.248-254
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• 2015

In this paper we propose an improved version of the computational integral imaging reconstruction (CIIR) for visualizing a partially occluded object by utilizing an image inpainting technique. In the proposed method the elemental images for a partially occluded three-dimensional (3D) object are recorded through the integral imaging pickup process. Next, the depth of occlusion within the elemental images is estimated using two different CIIR methods, and the weight mask pattern for occlusion is generated. After that, we apply our image inpainting technique to the recorded elemental images to fill in the occluding area with reliable data, using information from neighboring pixels. Finally, the inpainted elemental images for the occluded region are reconstructed using the CIIR process. To verify the validity of the proposed system, we carry out preliminary experiments in which faces are the objects. The experimental results reveal that the proposed system can dramatically improve the quality of a reconstructed CIIR image.

• Journal of the Optical Society of Korea
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• v.13 no.1
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• pp.139-145
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• 2009

Computational integral imaging (CII) is a new method for 3D imaging and visualization. However, it suffers from seriously poor image quality of the reconstructed image as the reconstructed image plane increases. In this paper, to overcome this problem, we propose a CII method based on a smart pixel mapping (SPM) technique for partially occluded 3D object recognition, in which the object to be recognized is located at far distance from the lenslet array. In the SPM-based CII, the use of SPM moves a far 3D object toward the near lenslet array and then improves the image quality of the reconstructed image. To show the usefulness of the proposed method, we carry out some experiments for occluded objects and present the experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1171-1176
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• 2011

This paper describes an analysis on the relationship between elemental image size and object locations in the computational integral imaging reconstruction and in the pickup using a periodically-distributed lenslet array. A sparse sampling effect arises from a periodically-distributed lenslet array in the pickup of 3D objects. The relationship between elemental image size and object location is also reported. Based on the analysis, a method to eliminate the sparse sampling is proposed. To show the effectiveness of the proposed method, experimental results are carried out. It turns out that the theory works.