• Proceedings of the KOSOMBE Conference
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• v.1989 no.05
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• pp.29-34
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• 1989

300 MHz proton NMR spectra of human blood plasma were analyzed by deconvolution of spectrum, and we compared its results with Fossel's test in normal (15 cases), liver cancer (14 cases) , and other cancer (14 cases) groups. This analysis had enabled us to obtain dynamic characteristics of each individual lipoprotein. As a result of deconvolution method, the VLDL and chylomicron intensity level were found to be elevated in the patients with liver cancer. Moment ratio values of $CH_2$ resonance in the raw spectrum were found to be higher than the normal group for patients with, malignant tumors other than liver cancer. These differences between the three groups could not be found in the conventional Fossel's test. We could simulate plasma spectra by addition of spectra of individual lipoproteins through deconvolution method. Further clinical trials in larger populations and additional biochemical method may shed new light on many of clinical and biochemical interests for knowing characteristics about lipoprotein not separated from blood and the background of Fossel test.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.6
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• pp.609-617
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• 2020

Non-destructive inspection using X-rays is used as a method to check the inside of products. In order to accurately inspect, a X-ray image requires a higher spatial resolution. However, the reduction in pixel size of the X-ray detector, which determines the spatial resolution, is time-consuming and expensive. In this regard, a DMM has been proposed to obtain an improved spatial resolution using the same X-ray detector. However, this has a limitation that the motion blur phenomenon, which is a decrease in spatial resolution. In this paper, motion blur was removed by applying Non-Blind Deconvolution to the DMM image, and the increase in spatial resolution was confirmed. DMM and Non-Blind Deconvolution were sequentially applied to X-ray images, confirming 62 % MTF value by an additional 29 % over 33 % of DMM only. In addition, SSIM and PSNR were compared to confirm the similarity to the 1/2 pixel detector image through 0.68 and 33.21 dB, respectively.

• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.838-848
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• 2014

In this paper, we conducted a cause analysis on boundary artifacts in image deconvolution. Results of the cause analysis show that boundary artifacts are caused not only by a misuse of boundary conditions but also by no use of the normalized backprojection. Results also showed that the correct use of boundary conditions does not necessarily remove boundary artifacts. Based on these observations, we suggest not to use any specific boundary conditions and to use the normalized backprojector for boundary artifact-free image deconvolution.

• Structural Engineering and Mechanics
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• v.21 no.3
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• pp.237-254
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• 2005

This article deals with the reconstruction of an impact force. This requires to take measurements from the impacted structures and then to deconvolve those signals from the impulse response function. More precisely, the purpose of the work described here is to analyse the method of deconvolution and the problems that it implies. Thus, it is highlighted that the associated deconvolution problem depends on the location of the measurement points: it is possible or not to reconstruct the force of impact in function of the location of this point. Then, the role of the antiresonances is linked up with this problem. The singular value decomposition is used to understand these difficulties. Numerical predictions are compared and validated with experiments.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.58.4-58.4
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• 2019

We present the application of the Point Spread Function (PSF) deconvolution method to the astronomical Integral Field Unit (IFU) Spectroscopy data focus on the restoration of the galaxy kinematics. We apply the Lucy-Richardson deconvolution algorithm to the 2D image at each wavelength slice. We make a set of mock IFU data which resemble the IFU observation to the model galaxies with a diverse combination of surface brightness profile, S/N, line-of-sight geometry and Line-Of-Sight Velocity Distribution (LOSVD). Using the mock IFU data, we demonstrate that the algorithm can effectively recover the stellar kinematics of the galaxy. We also show that lambda_R_e, the proxy of the spin parameter can be correctly measured from the deconvolved IFU data. Implementation of the algorithm to the actual SDSS-IV MaNGA IFU survey data exhibits the noticeable difference on the 2D LOSVD, geometry, lambda_R_e. The algorithm can be applied to any other regular-grid IFS data to extract the PSF-deconvolved spatial information.

• The Korean Journal of Nuclear Medicine
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• v.18 no.1
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• pp.9-17
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• 1984

The purpose of this study is to investigate significance of new method for quantification of left to right cardiac shunts using deconvolution analysis as an adjunct to gamma variate analysis in patients with bad bolus injection. In the present study, quantitative radionuclide angiocardiography (QRAC) was performed with and without deconvolution analysis (DA) in 37 patients with left to right shunt and 103 control patients without shunt. The results obtained were as follows; 1) The mean value of $Q_p/Q_s$ in 103 control patients was $1.10{\pm}0.12$ without DA, and was $1.01{\pm}0.03$ with DA. 2) Correlation(r) between oximetry and QRAC with DA was 0.87 and correlation(r) between oximetry and QRAC without DA was 0.61. 3) The 13 patients with left to right shunt, whose $Q_p/Q_s$ was greater than 3.0 by QRAC without DA, was studied by DA. Then the $Q_p/Q_s$ values were measurable in these 13 patients by DA and they showed significant correlation with oximetry. (r=0.68) The results indicate that deconvolution analysis technique for quantification of a left to right shunt provides more reliable and accurate shunt quantification, and reduces the influences of poor bolus injection.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.865-872
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• 2017

Recent advance in electronics and scintillators makes it possible to utilize the time-of-flight (TOF) information in improving image reconstruction of positron emission tomography(PET). In this paper, we propose a TOF-based fast image reconstruction method for PET. The proposed method uses the deconvolution of TOF data for each angle view and the rotational averaging of deconvolved images. Simulation results show an improved performance of the proposed method, as compared with filtered backprojection (FBP) method, TOF-FBP, and TOF version of expectation-maximization(EM) methods. Simulation results also show a great potentiality of the proposed method in limited angle tomography applications.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1750-1758
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• 2017

In super-resolution, various methods with Convolutional Neural Network(CNN) have recently been proposed. CNN based methods provide much higher image quality than conventional methods. Especially, VDSR outperforms other CNN based methods in terms of image quality. However, it requires a high computational complexity which prevents real-time processing. In this paper, the method to apply a deconvolution layer to VDSR is proposed to reduce computational complexity. Compared to original VDSR, the proposed method achieves the 4.46 times speed-up and its degradation in image quality is less than -0.1 dB which is negligible.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.413-421
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• 2015

Regularized Blind Deconvolution is a problem applicable in degraded images in order to bring the original image out of blur. Multichannel blind Deconvolution considered as an optimization problem. Each step in the optimization is considered as variable splitting problem using an algorithm called Alternating Minimization Algorithm. Each Step in the Variable splitting undergoes Augmented Lagrangian method (ALM) / Bregman Iterative method. Regularization is used where an ill posed problem converted into a well posed problem. Two well known regularizers are Tikhonov class and Total Variation (TV) / L2 model. TV can be isotropic and anisotropic, where isotropic for L2 norm and anisotropic for L1 norm. Based on many probabilistic model and Fourier Transforms Image deblurring can be solved. Here in this paper to improve the performance, we have used an adaptive regularization filtering and isotropic TV model Lp norm. Image deblurring is applicable in the areas such as medical image sensing, astrophotography, traffic signal monitoring, remote sensors, case investigation and even images that are taken using a digital camera / mobile cameras.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.319-322
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• 2016

We propose a parametric blind deconvolution method for bi-level images with unknown intensity levels that estimates unknown parameters for point spread functions and images by minimizing a penalized nonlinear least squares objective function based on normalized correlation coefficients and two regularization functions. Unlike conventional methods, the proposed method does not require knowledge about true intensity values. Moreover, the objective function of the proposed method can be effectively minimized, since it has the special structure of nonlinear least squares. We demonstrate the effectiveness of the proposed method through simulations and experiments.