• Korean Journal of Digital Imaging in Medicine
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• v.12 no.2
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• pp.139-143
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• 2010

Two-dimensional(2D) images like Multi Planar Reconstruction(MPR) Image or Maximum Intensity Projection(MIP) were used for the purpose of diagnosis, but MPR image's quality were limited due to its superior limit of Z-axis ability to produce permitted radiation exposure virtuous in the permitted time limit from the existing Spiral CT. However, in company with the development of the Multi Detector Computed Tomography(MDCT), we were able to get the Data with the equal amount of Voxel, also get varied reconstructions as in the aspect of our needs. This present study propose a reconstruction technique which is to extract a field using Region of interest(ROI) segmentation method for improvement of the quality of the medical image and after that reconstruct the concerned part using the four-directed symmetry method of the oval, than using the reconstructed data, reorganize the image by using the Curved MPR method. If current proposed method is used, it is highly effective because of its ability to accurately display the disease concerned part, which will reduce the decoding time and also effectively provide information based on the accuracy of the decode.

• Journal of Mechanical Science and Technology
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• v.14 no.1
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• pp.1-10
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• 2000

This work shows that it is possible to obtain information about more than one parameter from acoustic field information. A variety of ultrasonic Lamb wave modes were utilized to reconstruct thickness and density of an isotropic plate. An image reconstruction of one parameter (thickness of a plate) was carried out for four cases, i.e., the lowest symmetrical and anti symmetrical modes, and the fastest symmetrical and anti symmetrical Lamb waves among multiple modes. For two parameter reconstructions (thickness and density), the image processing was performed using the lowest symmetrical and antisymmetrical modes simultaneously. In this work, a modified version of algebraic reconstruction technique (ART), which is a form of finite-series expansion method, was employed to reconstruct the ultrasonically computed tomographic images. Results from several sample geometries are presented.

• ETRI Journal
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• v.41 no.1
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• pp.42-51
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• 2019

The rainbow hologram provides views of reconstruction with rainbow color within a large viewing zone. In our recent paper, a Fourier rainbow holographic display using diffraction grating and a white-light LED source was introduced. In this technique, the rainbow effect is realized by the dispersion of white-light source on diffraction grating, while the slit is implemented numerically by reducing the demands of the space-bandwidth product of the display. This paper presents a novel analysis on the visual perception of the Fourier rainbow holographic display using Wigner distribution. The view-dependent appearance of the image, including multispectral field of view and viewing zone, is investigated considering the observer and the display parameters. The resolution of the holographic view is also investigated. For this, a new quantitative assessment for image blur is introduced using Wigner distribution analysis. The analysis is supported with numerical simulations and experimentally captured optical reconstructions for the holograms of the computer model and real object generated with different slit size, reconstruction distance, and different observation conditions.

• Journal of Digital Contents Society
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• v.12 no.2
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• pp.157-164
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• 2011

The purpose of this study was to examine the usefulness of 3D reconstruction images in breast MRI by performing a quantitative comparative analysis in patients diagnosed with DCIS. On a 3.0T MR scanner, subtraction images and 3D reconstruction images were obtained from 20 patients histologically diagnosed with ductal carcinoma in situ (DCIS). The findings from the quantitative image analysis are the following: The 3D reconstruction images showed higher SNR at the lesion area, ductal area, and fat area that of the subtraction image. In addition, the CNR were not significantly different in the lesion area itself between the subtraction images and 3D reconstruction images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1246-1262
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• 2021

Recent studies have demonstrated the strong ability of deep convolutional neural networks (CNNs) to significantly boost the performance in single image super-resolution (SISR). The key concern is how to efficiently recover and utilize diverse information frequencies across multiple network layers, which is crucial to satisfying super-resolution image reconstructions. Hence, previous work made great efforts to potently incorporate hierarchical frequencies through various sophisticated architectures. Nevertheless, economical SISR also requires a capable structure design to balance between restoration accuracy and computational complexity, which is still a challenge for existing techniques. In this paper, we tackle this problem by proposing a competent architecture called Enhanced U-Net Network (EUN), which can yield ready-to-use features in miscellaneous frequencies and combine them comprehensively. In particular, the proposed building block for EUN is enhanced from U-Net, which can extract abundant information via multiple skip concatenations. The network configuration allows the pipeline to propagate information from lower layers to higher ones. Meanwhile, the block itself is committed to growing quite deep in layers, which empowers different types of information to spring from a single block. Furthermore, due to its strong advantage in distilling effective information, promising results are guaranteed with comparatively fewer filters. Comprehensive experiments manifest our model can achieve favorable performance over that of state-of-the-art methods, especially in terms of computational efficiency.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.362-362
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• 2010

Today, vast attention has been paid to periodic arrays of nanostructures due to their potential for applications such as memory with huge storage density. Such application requires large-scale fabrication of well ordered nano-sized structures. One of the most widely used methods for the ordered nanostructures is lithography. This top-down process, however, has the limit to reduce size. Here the promising alternative is the self-organization of ordered nano-sized structures such as large scale 2d carbon-induced reconstructions on W(110). In the present study, we report on the first well-resolved atomic resolution STM studies of the well-known R($15{\times}3$) and R($15{\times}12$) carbon induced reconstruction of the W(110). From the atomic image of R($15{\times}3$) for different values of tunneling gap resistance, we can tell there are no missing atoms in unit cells of R($15{\times}3$) and some atomic displacements are substantial from the clean W(110), even though not all the imaged position of atoms correspond to tungsten, but may include those of carbon. We are considering two cases; First case is related to lattice deformation, or top layer of W(110) is deformed in the process of relief of strain caused by random inserting of carbon atoms possibly in the interstitial position. In the second case, R($15{\times}3$) unit cell results from a coincidence lattice between clean W(110) substrate and tungsten carbide overlayer which has rectangular atomic arrangement and giving R($15{\times}3$) coincidence lattice. beta-W2C showing rectangular unit cell should be a candidate. Further, we report on new reconstructions. Unlike the well-known R($15{\times}12$) consisting of two parts, two inner structures between two "Backbone" structures. The new reconstruction, which we found for the first time, contains more parts between the "Backbone"s. Sometimes we can observe the reconstruction consists of only inner parts without "Backbone" parts. Thus, the observed reconstruction can be built by constructing of two types of "Lego"-like block. Moreover, the rectangle shape of "Backbone" transform to parallelogram-like shape over time, the so-called wavy-R($15{\times}12$). Adsorption of hydrogen can be the reason for this transformation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.10-23
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• 2009

The fundamental matrix and key frame selection are one of the most important techniques to recover full 3D reconstruction of objects from turntable sequences. This paper proposes a new algorithm that estimates a robust fundamental matrix for camera calibration from uncalibrated images taken under turn-table motion. Single axis turntable motion can be described in terms of its fixed entities. This provides new algorithms for computing the fundamental matrix. From the projective properties of the conics and fundamental matrix the Euclidean 3D coordinates of a point are obtained from geometric locus of the image points trajectories. Experimental results on real and virtual image sequences demonstrate good object reconstructions.

• Journal of Korea Entertainment Industry Association
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• v.5 no.1
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• pp.127-133
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• 2011

Characters in natural image are an important information with various context. Previous work of character region detection algorithms is not detect of character region in case of image complexity and the surrounding lighting, similar background to character, so this paper propose an method of character region detection in natural image using edge and connected component by morphological reconstructions. Firstly, we detect edge using Canny-edge detector and connected component with local min/max value by morphological reconstructed-operation in gray-scale image, and labeling each of detected connected component elements. lastly, detected candidate of text regions was merged for generation for one candidate text region, Final text region detected by checking the similarity and adjacency of neighbor of text candidate individual character. As the results of experiments, proposed algorithm improved the correctness of character regions detection using edge and connected components.

• ETRI Journal
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• v.40 no.6
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• pp.788-793
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• 2018

3D reconstruction of urban architecture, land, and roads is an important part of building a "digital city." Unmanned aerial vehicles (UAVs) are gradually replacing other platforms, such as satellites and aircraft, in geographical image collection; the reason for this is not only lower cost and higher efficiency, but also higher data accuracy and a larger amount of obtained information. Recent 3D reconstruction algorithms have a high degree of automation, but their computation time is long and the reconstruction models may have many voids. This paper decomposes the object into multiple regional parallel reconstructions using the clustering principle, to reduce the computation time and improve the model quality. It is proposed to detect the planar area under low resolution, and then reduce the number of point clouds in the complex area.

• Current Optics and Photonics
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• v.5 no.6
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• pp.680-685
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• 2021

We propose a technique that reconstructs a hologram whose pixel number is greater than the pixel numbers of a conventional image sensor. The pixel numbers of the hologram recorded by optical scanning holography (OSH) increases as the scan area becomes larger. The reconstruction time also increases drastically as the size of the hologram increases. The holographic information of a three-dimensional (3D) scene is distributed throughout the recorded hologram; this makes the simple divide-and-stitch approach fail. We propose a technique that reconstructs the hologram without loss of holographic information. First, we record the hologram of a 3D scene using OSH. Second, we segment the hologram into sub-holograms that contain complete holographic information. Third, we reconstruct the sub-holograms simultaneously. Finally, we rearrange the reconstructions of the sub-holograms.