• 대한방사선기술학회지:방사선기술과학
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• 제47권1호
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• pp.39-48
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• 2024

In this study, we optimized the FNLM algorithm through a simulation study and applied it to a phantom scanned by low-dose CT to evaluate whether the FNLM algorithm can be used to obtain improved image quality images. We optimized the FNLM algorithm with MASH phantom and FASH phantom, which the algorithm was applied with MATLAB, increasing the smoothing factor from 0.01 to 0.05 with increments of 0.001 and measuring COV, RMSE, and PSNR values of the phantoms. For both phantom, COV and RMSE decreased, and PSNR increased as the smoothing factor increased. Based on the above results, we optimized a smoothing factor value of 0.043 for the FNLM algorithm. Then we applied the optimized FNLM algorithm to low dose lung CT and lung CT under normal conditions. In both images, the COV decreased by 55.33 times and 5.08 times respectively, and we confirmed that the quality of the image of low dose CT applying the optimized FNLM algorithm was 5.08 times better than the image of lung CT under normal conditions. In conclusion, we found that the smoothing factor of 0.043 among the factors of the FNLM algorithm showed the best results and validated the performance by reducing the noise in the low-quality CT images due to low dose with the optimized FNLM algorithm.

• 한국의류학회지
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• 제16권4호
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• pp.393-403
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• 1992

This Study intended to provide positioning strategies of brand Image for ladies' ready to wear by analysing the perceptual dimensions of working women. The subjects were devided into two groups according to the fashion involvement, and in each group, a positioning map was composed by use of multidimensional scaling. 251 subjects of this study were gathered into stratified sample groups from working women in Seoul, being subdivided according to their each occupation and age. The data were analysed by frequency, percentage, average, $x^{2}-test$, 1-test, Factor Analysis, cronbach's $\alpha$. Also, KYST, PROFIT, PREFMAP for multidimensional scaling were used. The results were as follows. 1. Two groups were identified according to degree of fashion involvement: high-involvement group, and low-involvement group. 2. From the analysis of the similarity of brand image, high involvement group percieved greater difference in brand image than low involvement group. 3. From the analysis of the evaluation of brand attributes, the evaluations in self expression, fashionability, design, sales promotion activity, sociality, quality, fit showed differences bet-ween high involvement group and low involvement group. 4. From the analysis of the preference of brand image, the distribution of preference and ideal point were different between high involvement group and low involvement group.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2014년도 추계학술대회
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• pp.248-251
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• 2014

We develop the signal processing method for implementing the human perceptual variant on frequency and space. The human visual perceptual sensitivity varies as frequency components and the human perceivable resolution diminishes as the distances further from the eye-focused point. For realizing the frequency sensitivity, we developed the signal direction adaptive multiband energy scaling method to weight the frequency components. The low-pass filtering is designed on the developed energy scaling method for diminishing perceivable resolutions as the deviated distance from the eye-focused point. The developed method not only enhances the frequency components of image signals at the eye-focused region but also smoothes non-perceivable detailed image signals at non-focused regions. The proposed method is verified by the subjective and objective evaluations that it can improve human perceptual visual quality.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.178-183
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• 2009

Online image dictionary has become more and more popular in concepts cognition. However, for existing online systems, only very few images are manually picked to demonstrate the concepts. Currently, there is very little research found on automatically choosing large scale online images with the help of semantic analysis. In this paper, we propose a novel framework to utilize community-generated online multimedia content to visually illustrate certain concepts. Our proposed framework adapts various techniques, including the correlation analysis, semantic and visual clustering to produce sets of high quality, precise, diverse and representative images to visually translate a given concept. To make the best use of our results, a user interface is deployed, which displays the representative images according the latent semantic coherence. The objective and subjective evaluations show the feasibility and effectiveness of our approach.

• 인터넷정보학회논문지
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• 제9권1호
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• pp.171-177
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• 2008

본 연구에서는 베이어패턴을 가지는 보간 알고리듬들을 조도에 따른 성능을 실험을 통해 평가하였다. 보간 알고리듬으로는 양선형 컬러 보간 기법과 적응형 퍼지 컬러 보간 기법을 사용하였는데, 실험 결과 저조도하에서는 양선형 컬러 보간기법에 미디언 필터를 적용한 보간 기법이, 고조도하에서는 적응형 퍼지 컬러 보간 기법이, 그리고 그 사이의 조도 하에서는 양선형 컬러 보간 기법이 우수한 영상을 생성함을 알 수 있었다. 이 결과를 응용하여 입력되는 영상의 조도에 따라서 각각 다른 보간 알고리듬을 적용하여 영상을 보간하면 다양한 조도 하에서도 향상된 화질을 얻을 수 있을 것이다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2013년도 추계학술대회
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• pp.8-11
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• 2013

We implement the foveation and frequency sensitivity feature of human visual system in discrete cosine transform (DCT) domain. Resolution of human visual perception decays as distance from the eye-focused point, known as foveation property, and the middle frequency components give most pleasant image quality to human than the low and high frequency components, which is the frequency sensitivity property of human visual system. For satisfying the foveation property, we enhanced the local contrast at the focused regions and smoothed local contrast at the non-focused regions in the DCT domain without bringing the blocking and ringing artifacts. Moreover, the energies at each DCT frequency components is modified with various degree to fulfill the frequency sensitivity property. The proposed method is verified by the subjective and objective evaluations that it can the improve the human perceptual visual quality.

• 한국방사선학회논문지
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• 제1권1호
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• pp.31-37
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• 2007

본 연구의 목적은 CR(Computed Radiography)과 DR(Digital Radiography)장비의 각 Detector를 통해 획득된 영상의 화질을 비교 분석하기 위한 것이다. CR(AGFA MD 4.0 General plate, JAPAN)과 DR(HOLOGIC nDirect Ray, USA)에 대한 영상평가의 주요인자인 MTF(Modulation transfer function), NPS(Noise power spectrum), Photon fluence, DQE(Detective quantum efficiency)를 정량적인 값으로 도출하여 비교한 결과 CR이 DR보다 우수하게 나타났다. 본 연구의 결과는 CR과 DR장비의 Image quality를 정량적으로 평가할 수 있을 뿐만 아니라 이 장비들을 유지, 보수하는데도 도움이 될 것으로 사료된다.

• Restorative Dentistry and Endodontics
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• 제48권2호
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• pp.16.1-16.11
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• 2023

Objectives: The aim of this study was to evaluate the influence of peak kilovoltage (kVp) and a metal artifact reduction (MAR) tool on image quality and the diagnosis of vertical root fracture (VRF) in cone-beam computed tomography (CBCT). Materials and Methods: Twenty single-rooted human teeth filled with an intracanal metal post were divided into 2 groups: control (n = 10) and VRF (n = 10). Each tooth was placed into the socket of a dry mandible, and CBCT scans were acquired using a Picasso Trio varying the kVp (70, 80, 90, or 99), and the use of MAR (with or without). The examinations were assessed by 5 examiners for the diagnosis of VRF using a 5-point scale. A subjective evaluation of the expression of artifacts was done by comparing random axial images of the studied protocols. The results of the diagnoses were analyzed using 2-way analysis of variance and the Tukey post hoc test, the subjective evaluations were compared using the Friedman test, and intra-examiner reproducibility was evaluated using the weighted kappa test (α = 5%). Results: The kVp and MAR did not influence the diagnosis of VRF (p > 0.05). According to the subjective classification, the 99 kVp protocol with MAR demonstrated the least expression of artifacts, while the 70 kVp protocol without MAR led to the most artifacts. Conclusions: Protocols with higher kVp combined with MAR improved the image quality of CBCT examinations. However, those factors did not lead to an improvement in the diagnosis of VRF.

• 한국정보기술학회논문지
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• 제16권11호
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• pp.85-95
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• 2018

스마트폰의 보급이 확산되고 대중화됨에 따라 대부분의 사람들은 사진을 촬영하기 위해 모바일 카메라를 애용하고 있다. 하지만 저조도 환경에서 사진을 촬영할 때 광량이 부족한 이유로 원치 않는 잡음이 발생할 수 있다. 이런 잡음을 제거하기 위해, 최근 심층 합성곱 신경망에 기반한 잡음 제거 기법이 제안되었다. 이 기법은 성능 측면에서 큰 진전을 보였을지라도 여전히 텍스처 및 에지 표현 능력이 부족하다. 따라서 본 논문에서는 영상의 구조를 향상시키기 위해 에지의 방향 정보를 나타내는 호그 영상을 활용하고자 한다. 그리고 잡음 영상과 호그 영상을 스택으로 쌓은 후, 입력 텐서를 형성하여 심층 합성곱 신경망을 학습시키는 기법을 제안하고자 한다. 실험 결과를 통해, 제안한 기법은 기존의 기법보다 정량적인 화질 평가에서 더 우수한 결과를 얻을 수 있었으며 시각적인 측면에서도 텍스처 및 에지의 향상을 달성할 수 있었다.

• 디지털정책학회지
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• 제2권3호
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• pp.1-7
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• 2023

본 논문은 단일 영상을 이용하여 초해상도 방법을 수행하기 위해 질감-공간 영역을 분리한 뒤 세부정보를 중심으로 특징을 분류하는 방법을 제안한다. CNN(Convolutional Neural Network) 기반의 초해상도는 세부정보를 개선하기 위한 특징 추정 과정에서의 복잡한 절차와 중복된 특징 정보의 생성으로 인해 초해상도에서 가장 중요한 기준인 품질 저하가 발생할 수 있다. 제안하는 방법은 절차적 복잡성을 줄이고 중복 특징 정보의 생성을 최소화하여 초해상도 결과의 품질을 개선하기 위해 입력 영상을 질감과 공간의 두 채널로 분리하였다. 질감 채널에서는 세부정보 복원을 위해 다중스케일로 변환한 영상에 단계별 skip-connection을 적용한 잔차 블록 구조를 적용하여 특징 정제 과정을 수행함으로써 특징 추출을 개선하였고, 공간 채널에서는 평활화된 형태의 특징을 활용하여 잡음을 제거하고 구조적 특징을 유지하도록 하였다. 제안하는 방법을 이용해 실험한 결과 기존 초해상도 방법대비 PSNR 및 SSIM 성능 평가에서 향상된 결과를 보여 품질이 개선됨을 확인할 수 있었다.