• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2057-2062
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• 2024

Among photon counting detector (PCD)-based technologies, the K-edge subtraction (KES) method has a very high material decomposition efficiency. Yet, since the increase in noise in the X-ray image to which the KES method is applied is inevitable, research on image quality improvement is essential. Here, we modeled a block-matching and 3D filtering (BM3D) algorithm and applied it to PCD-based X-ray images with the improved KES (IKES) method. For PCD modeling, Monte Carlo simulation was used, and a phantom composed of iodine substances with different concentrations was designed. The IKES method was modeled by adding a log term to KES, and the X-ray image used for subtraction was obtained by applying the 3.0 keV range based on the K-edge region of iodine. As a result, the IKES image using the BM3D algorithm showed the lowest normalized noise power spectrum value. In addition, we confirmed that the contrast-to-noise ratio and no-reference-based evaluation results when the BM3D algorithm was applied to the IKES image were improved by 29.36 % and 20.56 %, respectively, compared to the noisy image. In conclusion, we demonstrated that the IKES imaging technique using a PCD-based detector and the BM3D algorithm fusion technique were very efficient for X-ray imaging.

• Journal of radiological science and technology
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• v.40 no.3
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• pp.443-451
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• 2017

Mammography is commonly used for screening early breast cancer. However, mammographic images, which depend on the physical properties of breast components, are limited to provide information about whether a lesion is malignant or benign. Although a dual-energy subtraction technique decomposes a certain material from a mixture, it increases radiation dose and degrades the accuracy of material decomposition. In this study, we simulated a breast phantom using attenuation characteristics, and we proposed a technique to enable the accurate material decomposition by applying weighting factors for the dual-energy mammography based on a photon-counting detector using a Monte Carlo simulation tool. We also evaluated the contrast and noise of simulated breast images for validating the proposed technique. As a result, the contrast for a malignant tumor in the dual-energy weighted subtraction technique was 0.98 and 1.06 times similar than those in the general mammography and dual-energy subtraction techniques, respectively. However the contrast between malignant and benign tumors dramatically increased 13.54 times due to the low contrast of a benign tumor. Therefore, the proposed technique can increase the material decomposition accuracy for malignant tumor and improve the diagnostic accuracy of mammography.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.2
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• pp.33-40
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• 2000

In this study, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D image into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that primitive elements are extracted too much to represent and to describe the shape. To solve these problems, a new shape decomposition algorithm using primitive elements that are similar to the geometrical characteristics of shape and 4 scan modes is proposed in this study. The multiple primitive elements as circle, square, and rhombus are extracted by using multiscan modes in a new algorithm. This algorithm have the characteristics that description error and number of primitive elements is reduced. Then, description efficiency is improved. The procedures is also simple and the processing time is reduced.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.67-75
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• 1999

In this paper, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D image into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that primitive elements are extracted too much to represent and to describe the shape. To solve these problems, a new shape decomposition algorithm using primitive elements tat are similar to the geometrical characteristics of shape and 4 scan modes is proposed in this study. The multiple primitive elements as circle, square, and rhombus are extracted by using multiscan modes in a new algorithm. This algorithm have chatacteristics that description error and number of primitive elements is reduced. Then, description efficiency is improved. The procedures is also simple and the processing time is reduced.

• The Journal of Natural Sciences
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• v.7
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• pp.27-35
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• 1995

This paper introduces a VLSI (Very Large Scale Integrated Circuit) implementation of the 2-D Discrete Cosine Transform (DCT) with an application to image and video coding. This implementation, which is based upon a state space model, uses both algorithm and data partitioning to achieve high efficiency. With this implementation, the amount of data transfers between the processing elements (PEs) are reduced and all the data transfers are limitted to be local. This system accepts the input as a progressively scanned data stream which reduces the hardware required for the input data control module. With proper ordering of computations, a matrix transposition between two matrix by matrix multiplications, which is required in many 2-D DCT systems based upon a row-column decomposition, can be also removed. The new implementation scheme makes it feasible to implement a single 2-D DCT VLSI chip which can be easily expanded for a larger 2-D DCT by cascading these chips.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.531-546
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• 2009

The main objective of this study is to analyse the polarimetric characteristics of the various terrain targets by ground-based polarimetric SAR system and to confirm the compatible and effective polarimetric analysis method to reveal the polarization properties of different terrain targets by the GB-SAR. The fully polarimetric GB-SAR data with HH, HV, VH, and VV components were focused using the Deramp-FFT (DF) algorithm. The focused GB-SAR images were processed by the H/A/$\alpha$ polarimetric decomposition and the combined H/$\alpha$ or H/A/$\alpha$ and Wishart classification method. The segmented image and distribution graphs in H/$\alpha$ plane using Cloude and Pottier's method showed a reliable result that this quad-polarization GB-SAR data could be useful to classified corresponding scattering mechanism. The H/$\alpha$-Wishart and H/A/$\alpha$-Wishart classification results showed that a natural media and an artificial target were discriminated by the combined classification, in particular, after applying multi-looking and the Lee refined speckle filter.

• Journal of radiological science and technology
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• v.44 no.5
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• pp.465-471
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• 2021

Dual-energy X-ray imaging (DEI) techniques can provide X-ray images that a certain material is suppressed or emphasized by combining two X-ray images obtained from two different x-ray spectrum. In this paper, a single-shot DEI, which uses stacked two detectors (i.e., multilayer detector), is proposed to reduce the patient dose and increase throughput in angiography. The polymethyl methacrylate (PMMA) and aluminum (Al) were selected as two basis materials for material decomposition, and material-specific images are reconstructed as a vector combination of these two materials. We investigate the contrast and noise performance of material-decomposed images using iodine phantoms with various concentrations and diameters. The single-shot DEI shows comparable performances to the conventional dual-shot DEI. In particular, the single-shot DEI shows edge enhancement in material-decomposed images due to the different spatial-resolution characteristics of upper and lower detectors. This study could be useful for designing the multilayer detector including scintillators and energy-separation filter for angiography purposes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2702-2719
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• 2013

A new optimal scheme based on curvelet transform is proposed for retinal image enhancement (RIE) using real-coded quantum genetic algorithm. Curvelet transform has better performance in representing edges than classical wavelet transform for its anisotropy and directional decomposition capabilities. For more precise reconstruction and better visualization, curvelet coefficients in corresponding subbands are modified by using a nonlinear enhancement mapping function. An automatic method is presented for selecting optimal parameter settings of the nonlinear mapping function via quantum genetic search strategy. The performance measures used in this paper provide some quantitative comparison among different RIE methods. The proposed method is tested on the DRIVE and STARE retinal databases and compared with some popular image enhancement methods. The experimental results demonstrate that proposed method can provide superior enhanced retinal image in terms of several image quantitative evaluation indexes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3C
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• pp.387-397
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• 2004

The wavelet transform providing both of the frequency and spatial information of an image is proved to be very much effective for the compression of images, and recently lot of studies on coding algorithms for images decomposed by the wavelet transform together with the multi-resolution theory are going on. This paper proposes a quadtree decomposition method of image compression applied to the images decomposed by wavelet transform by using the correlations between pixels and '0'data grouping. Since the coefficients obtained by the wavelet transform have high correlations between scales and high concentrations, the quadtree method can reduce the data quantity effectively. the experimental infrared image with 256${\times}$256 size and 8〔bit〕, was used to compare the performances of the existing and the proposed compression methods.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.145-150
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• 2008

This thesis explores the problem of reconstructing a three-dimensional(3D) scene given a set of images or image sequences of the scene. It describes efficient methods for the 3D reconstruction of static and dynamic scenes from stereo images, stereo image sequences, and images captured from multiple viewpoints. Novel methods for image-based and volumetric modelling approaches to 3D reconstruction are presented, with an emphasis on the development of efficient algorithm which produce high quality and accurate reconstructions. For image-based 3D reconstruction a novel energy minimisation scheme, Iterated Dynamic Programming, is presented for the efficient computation of strong local minima of discontinuity preserving energyy functions. Coupled with a novel morphological decomposition method and subregioning schemes for the efficient computation of a narrowband matching cost volume. the minimisation framework is applied to solve problems in stereo matching, stereo-temporal reconstruction, motion estimation, 2D image registration and 3D image registration. This thesis establishes Iterated Dynamic Programming as an efficient and effective energy minimisation scheme suitable for computer vision problems which involve finding correspondences across images. For 3D reconstruction from multiple view images with arbitrary camera placement, a novel volumetric modelling technique, Embedded Voxel Colouring, is presented that efficiently embeds all reconstructions of a 3D scene into a single output in a single scan of the volumetric space under exact visibility. An adaptive thresholding framework is also introduced for the computation of the optimal set of thresholds to obtain high quality 3D reconstructions. This thesis establishes the Embedded Voxel Colouring framework as a fast, efficient and effective method for 3D reconstruction from multiple view images.