• The Bulletin of The Korean Astronomical Society
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• v.38 no.1
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• pp.64.1-64.1
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• 2013

The point spread function (PSF) of an optical system is in general defined as a two-dimensional intensity distribution which results from a single point source at infinity. It is an important key for the evaluation of the optical performance of an astronomical telescope. The PSFs of the soft X-ray telescope (SXT) aboard Yohkoh were measured in a wide range of the field-of-view under the in-flight configuration at White Sands Missile Range prior to launching the satellite. It has been known that the SXT PSF has a sharp peak at the core and the intensity drops very fast as it goes distant from the center. Due to the combination of this sharp peak at the PSF core and the effect of undersampling by a large pixel size, a carefully designed method is requested in the examination of the PSF data. The pattern of the SXT PSF is determined by the fitting of a mathematical functional form to the pre-launch experimental data. The elliptical Moffat function has been adopted for the evaluation of the SXT PSF. It is revealed from our study that the SXT PSF shows a peculiar characteristics, and thus a careful consideration on the undersampling effect and also a proper choice of statistics are necessary for the determination of the best fit function of the PSF. Details on the on- and off-axis SXT PSF in the field-of-view will be introduced and discussed in our presentation.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1727-1730
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• 2003

In this paper we propose a sub-pixel point spread function (PSF) estimation method for a fully digital auto-focusing system. We assume that the amount of out-of-focus is the same along the concentric circle. In order to estimate the accurate PSF, sub-pixel information is considered in the proposed PSF estimation procedure. The feasibility of the proposed algorithm is experimentally demonstrated.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.2
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• pp.57-62
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• 1999

Estimation of the point spread function (PSF) is one of the main research topic of image processing, because it determines the performance of the auto-focusing system. In this paper, a new algorithm for PSF estimation is proposed, and its application to image restoration is also presented. The procedure for complete realization of the auto-focusing system consists of two steps: PSF estimation based on edge classification, and image restoration using the estimated PSF. More specifically, we divide imput image into multiple small image or block, estimate unit step response and average them on the blocks which contain edge, and estimate 2-dimensional isotropic PSF from the 1 dimensional step response. Finally we obtain in-focused image by using image restoration based on the estimated PSF.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.7-13
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• 2009

This paper presents a circularly symmetric point spread function (PSF) estimation technique for a fully digital auto-focusing system. The proposed algorithm provides realistic, unsupervised PSF estimation by establishing the relationship between one-dimensional ideal step response and two-dimensional circularly symmetric PSF.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.1
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• pp.43-45
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• 2018

Purpose In this study, we evaluated image by applying with and without point spread function algorithm(PSF) according to reconstruction type. Materials and Methods Biograph mMR (Siemens, Germany) was used as PET/MR scanner. For phantom study, we used NEMA IEC Body phantom maintaining radioactivity ratio (hotsphere:background = 8:1). To evaluate phantom image quality, percent contrast recovery and signal to noise ratio (SNR) were used by drawing ROI to 4 spheres. In clinical study, the 20 patients who underwent simultaneous PET/MR was selected and set the ROI at liver. we evaluated images as SNR. Results In the phantom results, The percent contrast recovery applying PSF algoritm was high 5 % compared to without PSF algoritm and SNR was also high 11 %. In the clinical study result, we confirmed that The SNR applying PSF algoritm was high 5 % compared to without PSF algoritm. Conclusion We need to simulate a lot of phantom study and clinical analysis to improve image quality for PET/MRI.

• Journal of The Korean Astronomical Society
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• v.36 no.spc1
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• pp.117-124
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• 2003

Pre-launch calibration data have been analyzed for evaluating the point spread function (PSF) of Yohkoh Soft X-ray Telescope (SXT). Especially, it is found crucial that the effect of undersampling should be treated properly. The best fit solution of the SXT PSF, which is modeled by an elliptical Moffat function, has been derived by the comparison with the ground experiment data. In order to examine the off-axis variation of the SXT PSF, we need to define in advance the location of the optical axis on the CCD. According to the previous studies, the off-axis variation of effective area (the vignetting function) may be approximated either by two non-concentric cones or by a cone with some flat distortions. There have been, however, no fully approved representations for the SXT vignetting effect. The effect of the shift of the optical axis from the geometrical center of the telescope is investigated by numerical simulation. It is revealed from our study that the full width at half maximum (FWHM) of the SXT PSF stays nearly constant within an error bound over the central area of the CCD where the solar disk is located.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.7-10
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• 2003

This paper proposes the multiple objects focusing algorithm. Given multiple objects at different distances from a camera, we assume that one object is well-focused and the others are out-of-focused. The proposed auto-focusing algorithm is summarized as follows: (i) detects edges from an input image, (ⅱ) estimates the radius of PSF (Point Spread Function) across the edge, (ⅲ) gather edge points having same radius of PSF, (ⅳ) segments the image into regions with the same radius of PSF, and (ⅴ) restores the each segmented region using the corresponding PSF.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.93.2-93.2
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• 2012

Point Spread Function (PSF) is one of the most important optical characteristics for describing the performance of a telescope. And a concept of subpixelization is inevitable in evaluating the undersampled PSF (Shin and Sakurai 2009). Then, the internal structure of Yohkoh SXT CCD pixel is not uniform: For the top half of pixel area, the X-ray should pass a so-called gate structure where the charges are transferred to an output amplifier. This gate structure shows energy-dependent sensitivity (Tsuneta et al. 1991). For example, for Al-K (8.34 A) X-ray emission, the transmission of the polysilicon gate is about 0.9. Also, for the peak coronal response of the SXT thin filters, around 17 angstrom (0.729 keV), the transmission of the gate is about 0.6, falling off sharply towards longer wavelengths. It should be noted that this spectrally dependent non-uniform response of each CCD pixel will certainly have a noticeable effect on the properties of the PSF at longer wavelengths. Therefore, especially for analyzing the undersampled PSF of low energy source, a careful consideration of non-uniform internal pixel structure is required in determining the shape of the PSF core. The details on the effect of gate structure will be introduced in our presentation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.11a
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• pp.139-143
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• 1997

본 논문에서는 점확산함수(point spread function; PSF)의 추정을 기반으로 한 완전한 자동초점 시스템을 제안한다. 초점이 맞지 않은 영상의 정확한 PSF의 추정을 위해서, 입력 영상을 부영상으로 분할하고, 에지를 가진 부영상들의 계수함수 응답의 평균을 취한다. 초점이 맞지 않은 열화로 발생하는 PSF는 보통 영상이 물체와 배경간에 선형의 경계를 가지고 있다는 가정하에 에지의 방향을 따라 평균되어진 계단함수 응답의 차이를 따라 추정되어진다. 이렇게 예측된 PSF를 사용하여 영상복원 필터는 제한적 최소 제곱의 접근방법을 통해 구현되어진다.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.145-150
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• 2022

The main purpose of this work was to restore the blurry chest CT images by applying a blind deconvolution algorithm. In general, image restoration is the procedure of improving the degraded image to get the true or original image. In this regard, we focused on a blind deblurring approach with chest CT imaging by using digital image processing in MATLAB, which the blind deconvolution technique performed without any whole knowledge or information as to the fundamental point spread function (PSF). For our approach, we acquired 30 chest CT images from the public source and applied three type's PSFs for finding the true image and the original PSF. The observed image might be convolved with an isotropic gaussian PSF or motion blurring PSF and the original image. The PSFs are assumed as a black box, hence restoring the image is called blind deconvolution. For the 30 iteration times, we analyzed diverse sizes of the PSF and tried to approximate the true PSF and the original image. For improving the ringing effect, we employed the weighted function by using the sobel filter. The results was compared with the three criteria including mean squared error (MSE), root mean squared error (RMSE) and peak signal-to-noise ratio (PSNR), which all values of the optimal-sized image outperformed those that the other reconstructed two-sized images. Therefore, we improved the blurring chest CT image by using the blind deconvolutin algorithm for optimal approach.