• 방송공학회논문지
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• 제9권2호
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• pp.131-141
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• 2004

기존의 양안식 스테레오 비디오는 장면 내에 매우 큰 변이를 가지는 물체가 존재할 경우에 시각피로를 유발하여 오랜 시간 동안 시청하기가 어렵게 된다. 이러한 시각피로를 개선하기 위한 하나의 방법으로서 본 논문에서는 변이 기반 비대칭 필터링 기법을 제안한다. 제안한 방법은 좌우영상 중 한쪽 눈에 해당하는 영상에만 필터링을 수행하고, 필터링 수준을 스테레오 영상 사이에서 구해진 변이 정보에 의해 조절한다. 제안한 기법의 시각 피로도 및 영상의 선명도에 미치는 영향을 주관적 평가에 의해 조사한 결과, 적절한 조건 하에 제안한 기법을 주시되지 않은 시차가 큰 영역에 적용할 경우 화질은 원영상의 화질을 유지하면서 시각 피로가 개선되는 효과를 얻을 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.907-923
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• 2020

For the severe haze situation in the Beijing-Tianjin-Hebei region, conventional fine particulate matter (PM2.5) concentration prediction methods based on pollutant data face problems such as incomplete data, which may lead to poor prediction performance. Therefore, this paper proposes a method of predicting the PM2.5 concentration based on image analysis technology that combines image data, which can reflect the original weather conditions, with currently popular machine learning methods. First, based on local parameter estimation, autoregressive (AR) model analysis and local estimation of the increase in image blur, we extract features from the weather images using an approach inspired by free energy and a no-reference robust metric model. Next, we compare the coefficient energy and contrast difference of each pixel in the AR model and then use the percentages to calculate the image sharpness to derive the overall mass fraction. Furthermore, the results are compared. The relationship between residual value and PM2.5 concentration is fitted by generalized Gauss distribution (GGD) model. Finally, nonlinear mapping is performed via the wavelet neural network (WNN) method to obtain the PM2.5 concentration. Experimental results obtained on real data show that the proposed method offers an improved prediction accuracy and lower root mean square error (RMSE).

• 대한방사선기술학회지:방사선기술과학
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• 제14권1호
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• pp.61-72
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• 1991

In this paper, the rotating plate method extracting signal and reconstructing original image was proposed. The rotating methode has cell detector array each of which has used in the medical diagnosis X-ray photography. The major problem using the simple horizontal moving or non-moving methode is the size and number of detector cells which have the considerable affection on the sharpness and resolution of the reconstructed image. Secondary, the estimated pixel values of non-detected real points which are placed between detector cells will be the distorted pixels in the reconstructed image. Therefore, the proposed rotating plate method has the exact distribution on the uncertain pixels which were reconstructed by conventional methods to solve there problems. And then, the image using the rotated plate's cell out put signal was reconstructed on the computer simulation. The method will rotated the detector array plate to solve the reconstruction from the detector size and number of conventional methods. The result of simulation has estimated the original pixel position and 81 pixel/mm resolution which the reconsiderlation of the detector's moving orientation, the proposed method has 25 pixel/mm resolution. These results have been represented by 3-D computer graphics.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1999년도 KOBA 방송기술 워크샵 KOBA Broadcasting Technology Workshop
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• pp.83-88
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• 1999

In this paper, a novel gray-scale lossless image coder combining context-based minimum mean squared error (MMSE) prediction and entropy coding is proposed. To obtain context of prediction, this paper first defines directional difference according to sharpness of edge and gradients of localities of image data. Classification of 4 directional differences forms“geometry context”model which characterizes two-dimensional general image behaviors such as directional edge region, smooth region or texture. Based on this context model, adaptive DPCM prediction coefficients are calculated in MMSE sense and the prediction is performed. The MMSE method on context-by-context basis is more in accord with minimum entropy condition, which is one of the major objectives of the predictive coding. In entropy coding stage, context modeling method also gives useful performance. To reduce the statistical redundancy of the residual image, many contexts are preset to take full advantage of conditional probability in entropy coding and merged into small number of context in efficient way for complexity reduction. The proposed lossless coding scheme slightly outperforms the CALIC, which is the state-of-the-art, in compression ratio.

• Korean Journal of Radiology
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• 제22권11호
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• pp.1850-1857
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• 2021

Objective: The purpose of this study was to assess whether a deep learning (DL) algorithm could enable simultaneous noise reduction and edge sharpening in low-dose lumbar spine CT. Materials and Methods: This retrospective study included 52 patients (26 male and 26 female; median age, 60.5 years) who had undergone CT-guided lumbar bone biopsy between October 2015 and April 2020. Initial 100-mAs survey images and 50-mAs intraprocedural images were reconstructed by filtered back projection. Denoising was performed using a vendor-agnostic DL model (ClariCT.AI^TM, ClariPI) for the 50-mAS images, and the 50-mAs, denoised 50-mAs, and 100-mAs CT images were compared. Noise, signal-to-noise ratio (SNR), and edge rise distance (ERD) for image sharpness were measured. The data were summarized as the mean ± standard deviation for these parameters. Two musculoskeletal radiologists assessed the visibility of the normal anatomical structures. Results: Noise was lower in the denoised 50-mAs images (36.38 ± 7.03 Hounsfield unit [HU]) than the 50-mAs (93.33 ± 25.36 HU) and 100-mAs (63.33 ± 16.09 HU) images (p < 0.001). The SNRs for the images in descending order were as follows: denoised 50-mAs (1.46 ± 0.54), 100-mAs (0.99 ± 0.34), and 50-mAs (0.58 ± 0.18) images (p < 0.001). The denoised 50-mAs images had better edge sharpness than the 100-mAs images at the vertebral body (ERD; 0.94 ± 0.2 mm vs. 1.05 ± 0.24 mm, p = 0.036) and the psoas (ERD; 0.42 ± 0.09 mm vs. 0.50 ± 0.12 mm, p = 0.002). The denoised 50-mAs images significantly improved the visualization of the normal anatomical structures (p < 0.001). Conclusion: DL-based reconstruction may enable simultaneous noise reduction and improvement in image quality with the preservation of edge sharpness on low-dose lumbar spine CT. Investigations on further radiation dose reduction and the clinical applicability of this technique are warranted.

• 전자공학회논문지 IE
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• 제48권1호
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• pp.51-56
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• 2011

본 연구에서는 흉부 CR 영상에 대하여 다양한 디지털 영상처리 기법을 가하여 영상의 질을 개선시키고 화질 평가를 수행하였다. 또한 흉부 CR 영상의 선예도를 개선하기 위해서 고주파 강조 필터링과 히스토그램 평활화를 MATLAB으로 구현하여 시뮬레이션 한 결과 고주파 강조 필터링과 히스토그램 평활화를 통해서 원영상의 대조도가 개선되었다. 디지털영상처리에 의해 화질의 개선된 정도를 평가하기 위해서 영상의 관찰에 의한 주관적 평가기법을 이용하였다. 신호 또는 병소가 있는 영상에서 신호 또는 병소를 발견할 확률로 감도를 계산하였다. 고주파 강조 필터링과 히스토그램 평활화가 수행된 영상의 감도는 원영상보다 개선되었고, 의료영상에서 수행된 디지털 영상처리는 영상의 질을 향상시켰다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.180-183
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• 2002

In this paper, we propose new unsharp masking technique based on the multiscale gradient planes. The unsharp masking technique is implemented as a high-pass filter and improves the sharpness of degraded images. However, the conventional unsharp masking enhances the noise component simultaneously. To reduce the noise influence, we introduce the edge information from the difference of the gradient values between two consecutive scales of the multiscale gradient. The multiscale gradient indicates the presence of image edges as the ratio between the gradients between two different scales by its multiscale nature. The noise reduction of the proposed method does not depend on the variance of images and noises. In experiment, we demonstrate enhancement results for blurred noisy images and compare with the conventional cubic unsharp masking technique.

• 한국분무공학회지
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• 제10권3호
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• pp.17-28
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• 2005

The Holographic Particle Velocimetry system can be a promising optical tool for the measurements of three dimensional particle velocities. In this study, diffused illumination holographic system to measure the sizes and 3D velocities of moving particles based on automatic image processing was developed. First of all basic optical systems for pulse laser recording, continuous laser reconstruction, and image acquisition, were constructed. To determine the position of particles in the optical axis, new three auto-focusing parameters(AEP), namely, Correlation Coefficient, Sharpness Index, and Depth Intensity were introduced and verified. The developed system was applied to spray droplets to validate the capability of the system. Three dimensional positions of particles viewed from two sides were decided using AFP and then 3D velocities of Particles were extracted by particle tracking algorithm. Comparison of measurement results of sizes and 3D velocities of particles with those obtained by laser instrument, PDPA, showed good consistency of the developed holographic system.

• Journal of Information Processing Systems
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• 제15권1호
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• pp.47-54
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• 2019

This study is concerned with the mechanism and structure of an optical microscope and an automatic multi-focus algorithm for automatically selecting sharp images from multiple foci of a cell. To obtain precise cell images quickly, a z-axis actuator with a resolution of $0.1{\mu}m$ was designed to control an optical microscope Moreover, a lighting control system was constructed to select the color and brightness of light that best suit the object being viewed. Cell images are captured by the instrument and the sharpness of each image is determined using Gaussian and Laplacian filters. Next, cubic spline interpolation and peak detection algorithms are applied to automatically find the most vivid points among multiple images of a single object. A cancer cell imaging experiment using propidium iodide staining confirmed that a sharp multipoint image can be obtained using this microscope. The proposed system is expected to save time and effort required to extract suitable cell images and increase the convenience of cell analysis.

• 대한전자공학회논문지SP
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• 제46권6호
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• pp.112-122
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• 2009

본 논문에서는 베이글릿-웨이블릿 분석(vaguelette-wavelet decomposition; VWD)을 이용한 공간-주파수 적응적 영상복원 알고리듬을 제안한다. 제안한 알고리듬은 웨이블릿 계수의 공간적 정보를 이용하여 평탄 영역과 에지 영역을 분리하고, 적응적 웨이블릿 계수축소(wavelet shrinkage)를 통해 잡음 성분을 억제한다. 뿐만 아니라, 에지 영역에서는 엔트로피(entropy)를 적용 하여 웨이블릿 부대역의 잡음 성분을 추정하고, 부대역 간의 상관관계를 이용하여 잡음 성분을 억제한다. 이렇게 억제된 웨이블릿 계수의 베이글릿 역변환을 통해 영상을 복원 할 수 있다. 제안한 알고리듬에 사용되는 베이글릿 함수는 잡음을 추정 및 억제 할 수 있을 뿐만 아니라 세밀한 에지 성분의 보존이 가능하도록 변형을 한다. 실험결과에서는 제안한 알고리듬이 잡음에 강건하고, 세밀한 에지 성분을 보전하면서 효과적으로 열화된 영상을 복원할 수 있음을 보여준다.