• 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.

• Molecules and Cells
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• v.42 no.2
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• pp.104-112
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• 2019

Tracking the fate of individual cells and their progeny through lineage tracing has been widely used to investigate various biological processes including embryonic development, homeostatic tissue turnover, and stem cell function in regeneration and disease. Conventional lineage tracing involves the marking of cells either with dyes or nucleoside analogues or genetic marking with fluorescent and/or colorimetric protein reporters. Both are imaging-based approaches that have played a crucial role in the field of developmental biology as well as adult stem cell biology. However, imaging-based lineage tracing approaches are limited by their scalability and the lack of molecular information underlying fate transitions. Recently, computational biology approaches have been combined with diverse tracing methods to overcome these limitations and so provide high-order scalability and a wealth of molecular information. In this review, we will introduce such novel computational methods, starting from single-cell RNA sequencing-based lineage analysis to DNA barcoding or genetic scar analysis. These novel approaches are complementary to conventional imaging-based approaches and enable us to study the lineage relationships of numerous cell types during vertebrate, and in particular human, development and disease.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.991-996
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• 2007

Recently, a computational reconstruction method using an integral imaging technique, which is a promise three-dimensional display technique, has been actively researched. This method is that 3-D images can be digitally reconstructed at the required output planes by superposition of all of the inversely enlarged elemental images by using a hypothetical pinhole array model. However, the conventional method mostly yields reconstructed images having a low-resolution, because there are some intensity irregularities with a grid structure at the reconstructed mage plane by using square-type elemental images. In this paper, to overcome this problem, we propose a novel computational integral imaging reconstruction (CIIR) method using round-type mapping model. Proposed CIIR method can overcome problems of non-uniformly reconstructed images caused from the conventional method and improve the resolution of 3-D images. To show the usefulness of the proposed method, both computational experiment and optical experiment are carried out and their results are presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.6
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• pp.1363-1368
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• 2011

This paper describes an analysis on the granular noise in pixel-to-pixel mapping-based computational integral imaging. The pixel mapping-based method provides a high-resolution reconstructed images and also its computational cost is very lower than the previous back-projection-based method. In this paper, a signal model for the pixel mapping-based method is introduced, which defines and analyzes the granular noise. Computer experiments provides the granular noise properties based on the proposed signal model. The experimental results indicates that the granular noise pattern differs from that of the back-projection based method. The results is also utilized in the pixel mapping-based method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.1
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• pp.121-126
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• 2009

Plane-based computational integral imaging (CIIR) provides the reconstruction of depth-dependent 3D plane images. However, it has problem degrading the resolution of reconstructed images due to the artifact noise according to the depth. In this paper, to overcome this problem, a signal model for plane-based CIIR is explain. Also the compensation process is introduced to remove the noise caused from CIIR. Computational experiments show that we analyze the characteristics of noise in the reconstructed image of 2D Gaussian image and the high-resolution images can be obtained by using the compensation process.

• 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 the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2271-2276
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• 2008

In this paper, we propose a computational integral imaging reconstruction (CIIR) method based on scale-cariant magnification technique for resolution-enhanced 3D images. First, we introduce an interference problem among elemental images in CIIR. Magnification by a large factor causes inference among elemental images when they are applied to the superposition process. Thus, the resolution of reconstructed images is limited. To overcome the interference problem, we propose a method to calculate a minimum magnification factor while CIIR is still valid. Magnification by a new factor enables the Proposed method to reconstruct resolution-enhanced images. In addition, the computational load of the proposed method is less than that of the previous method. To confirm the feasibility of the proposed method, some experiments are carried out and the results are presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1853-1859
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• 2008

In this paper, we propose a novel method to improve the visual quality of reconstructed images for 3D pattern recognition based on the computational integral imaging reconstruction (CIIR). The proposed CIIR method provides improved 3D reconstructed images by superimposing magnified elemental images by a combination of a round mapping model and image interpolation algorithms. To objectively evaluate the proposed method, we introduce an experimental framework for a computational pickup process and a CIIR process using a Gaussian function and evaluate the proposed method. We also carry out experiments on 3D objects and present their results.

• Journal of applied mathematics & informatics
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• v.41 no.3
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• pp.603-613
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• 2023

In this paper, the concept of geodesic centered tractography is explored for diffusion tensor imaging (DTI). In DTI, where geodesics has been tracked and the inverse of the fourth-order diffusion tensor is inured to determine the diversity. Specifically, we investigated geodesic tractography technique for High Angular Resolution Diffusion Imaging (HARDI). Riemannian geometry can be extended to a direction-dependent metric using Finsler geometry. Euler Lagrange geodesic calculations have been derived by Finsler geometry, which is expressed as HARDI in sixth order tensor.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.718-721
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• 2008

Novel computational integral imaging technique with enhanced depth sensitivity is proposed. For each lateral position at a given depth plane, the dissimilarity between corresponding pixels of the elemental images is measured and used as a suppressing factor for that position. Experimental and simulation results show that reconstructed depth image on the incorrect depth plane is effectively suppressed.