• 제목/요약/키워드: image deblurring

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Medical imaging을 위한 영상 보간 방법의 비교 (COMPARISON OF INTERPOLATION METHODS for MEDICAL IMAGING)

  • 이병길;하영호
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1990년도 추계학술대회
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    • pp.38-41
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    • 1990
  • A new spline function for resampling discrete signal adaptively is proposed. In general, B-spline function is used for an image interpolation because of its smoothness and continuity, but accompanies a large amount of blurring effect. Hence, we developed a new spline function to remedy this effect, with two procedures ; deblurring of Gaussian blurring and diminishing of aliasing effect caused by deblurring procedure. The proposed function has a parametric expression with $\alpha$ which is related to the variance of Gaussian blurring model. Locally adaptive resampling scheme is obtained by changing a according to statistical characteristics of an image. The proposed, interpolation function shows edge-sharpening effect as well as noise smoothing, with comparison to the conventional schemes.

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Regularized Multichannel Blind Deconvolution Using Alternating Minimization

  • James, Soniya;Maik, Vivek;Karibassappa, K.;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
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    • 제4권6호
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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.

흉부 컴퓨터단층촬영 영상에서 블라인드 디컨볼루션 알고리즘 최적화 방법에 대한 연구 (Analysis on Optimal Approach of Blind Deconvolution Algorithm in Chest CT Imaging)

  • 이영준;민정환
    • 대한방사선기술학회지:방사선기술과학
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    • 제45권2호
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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.

GLOBAL GENERALIZED CROSS VALIDATION IN THE PRECONDITIONED GL-LSQR

  • Chung, Seiyoung;Oh, SeYoung;Kwon, SunJoo
    • 충청수학회지
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    • 제32권1호
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    • pp.149-156
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    • 2019
  • This paper present the global generalized cross validation as the appropriate choice of the regularization parameter in the preconditioned Gl-LSQR method in solving image deblurring problems. The regularization parameter, chosen from the global generalized cross validation, with preconditioned Gl-LSQR method can give better reconstructions of the true image than other parameters considered in this study.

A WEIGHTED GLOBAL GENERALIZED CROSS VALIDATION FOR GL-CGLS REGULARIZATION

  • Chung, Seiyoung;Kwon, SunJoo;Oh, SeYoung
    • 충청수학회지
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    • 제29권1호
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    • pp.59-71
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    • 2016
  • To obtain more accurate approximation of the true images in the deblurring problems, the weighted global generalized cross validation(GCV) function to the inverse problem with multiple right-hand sides is suggested as an efficient way to determine the regularization parameter. We analyze the experimental results for many test problems and was able to obtain the globally useful range of the weight when the preconditioned global conjugate gradient linear least squares(Gl-CGLS) method with the weighted global GCV function is applied.

쇼크 필터와 합성곱 신경망 기반의 균일 모션 디블러링 기법 (Uniform Motion Deblurring using Shock Filter and Convolutional Neural Network)

  • 정민소;정제창
    • 방송공학회논문지
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    • 제23권4호
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    • pp.484-494
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    • 2018
  • Cho 등의 균일 모션 블러 제거 알고리듬은 영상 내 외곽선 영역을 선명하게 복원하지 못한다는 문제점이 있다. 이러한 문제점을 극복하기 위해 본 논문에서는 한 장의 정지 영상에서 발생하는 블러 (Blur)현상을 블러된 계단형 신호를 뚜렷한 외곽선으로 복원해주는 쇼크 필터 (Shock filter)와 영상에서 특징을 추출하여 학습하는 합성곱 신경망 (Convolutional Neural Network: CNN)을 이용하여 선명한 영상을 복원하고 이 영상으로부터 균일 모션 (Uniform motion) 블러를 측정하여 영상 내 블러 현상을 제거하는 효과적인 알고리듬을 제안하고자 한다. 제안된 알고리듬은 쇼크 필터와 합성곱 신경망을 이용하여 선명한 영상을 복원함으로써 기존 알고리듬의 단점을 개선하였다. 실험 결과를 통해 제안하는 알고리듬이 기존 알고리듬에 비해 객관적 및 주관적인 평가에서 우수한 복원 성능을 나타냄을 확인하였다.

볼록거울 영상에서 일어나는 영상 겹침 극복을 위한 비선형적 디블러링 알고리즘 (Nonlinear Deblurring Algorithm on Convex-Mirror Image for Reducing Occlusion)

  • 이인정
    • 정보처리학회논문지A
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    • 제13A권5호
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    • pp.429-434
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    • 2006
  • 볼록거울을 사용하여 CCTV시스템을 만들면 카메라 수를 줄이는 효과가 있다. 이 경우 볼록거울 영상은 횐 영상이므로 평면영상처럼 변환해야 한다. 이 경우에, 중앙에 비추인 영상은 평면 영상으로 변환 후에도 왜곡이 거의 없지만 거울의 테두리 부근에서 얻은 영상을 변환하면 왜곡이 심하게 나타나서 영상 내의 물체를 식별하기가 어려워진다. 이는 볼록거울의 특성으로, 입사각이 겹쳐지면서 생기는 영상 겹침이 일어나기 때문이다. 거기에다 먼 곳에서 오는 빛의 산란과 그로 인한 블러링이 영상을 왜곡 시키는 요인이 된다. 본 논문에서는 이러한 왜곡을 극복하기 위해 편이 등고선 확장 방법과 비선형 파동방정식의 후진대입 해를 이용하여 빛의 산란효과를 줄이는 방법을 제안한다. 보통의 선형적 방법으로는 주파수 영역에서 푸리에 변수가 겹치는 신호로부터 블러드 노이즈를 분리해 낼 수가 없음은 알려져 있다. 그러나 비선형 변분법적 공식을 사용하면 그 블러드 노이즈 제거에 큰 효과를 볼 수 있다. 본 논문의 제안요소는 이 변분법적 공식을 사용하기 전에 편이 등고선 확장정리를 사용하여 영상겹침을 줄이고 파동방정식을 사용하여 산란효과를 줄이는 방법을 사용하는 것이다. 제안 결과를 분석하기 위해 PSNR값을 조사하였더니 파동방정식을 사용한 결과가 사용하지 않은 기존결과에 비해 4dB정도 개선된 값을 보였다.

THE FAST TRUNCATED LAGRANGE METHOD FOR IMAGE DEBLURRING WITH ANTIREFLECTIVE BOUNDARY CONDITIONS

  • Oh, SeYoung;Kwon, SunJoo
    • 충청수학회지
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    • 제31권1호
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    • pp.137-149
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    • 2018
  • In this paper, under the assumption of the symmetry point spread function, antireflective boundary conditions(AR-BCs) are considered in connection with the fast truncated Lagrange(FTL) method. The FTL method is proposed as an image restoration method for large-scale ill-conditioned BTTB(block Toeplitz with Toeplitz block) and BTHHTB(block Toeplitz-plus-Hankel matrix with Toeplitz-plus-Hankel blocks) linear systems([13, 17]). The implementation and efficiency of the FTL method in the AR-BCs are further illustrated. Especially, by employing the AR-BCs, both the continuity of the image and the continuity of its normal derivative are preserved at the boundary. A reconstructed image with less artifacts at the boundary is obtained as a result.