• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.271-280
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• 2004

This paper presents a new iterative image restoration algorithm with removal of boundary/object-oriented ringing, The proposed method is based on CGM(Conjugate Gradient Method) iterations with inter-wavelet shrinkage. The proposed method provides a fast restoration as much as CGM, while having adaptive do-noising and do-ringing by using wavelet shrinkage. In order to have effective do-noising and do-ringing simultaneously, the proposed method uses a space-dependent shrinkage rule. The improved performance of the proposed method over more traditional iterative image restoration algorithms such as LR(Lucy-Richardson) and CGM in do-noising and do-ringing is shown through numerical experiments.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.400-407
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• 2019

In this paper, the shadow detection and reconstruction method are proposed using intrinsic image, which does not change the essential characteristics under the influence of various illuminance, and multi-scale gamma correction. The shadow detection was estimated by the pixel change information between a grayscale and an intrinsic image of the color image, and the brightness of the image were adjusted by gamma correction in the shadow restoration process. Multi-scale gamma correction is performed for each channel of a color image due to the fact that the saturation can be changed by nonlinear adjustment to individual pixel values. Multi-scale gamma values are estimated based on the information of the crossed edge between shadows and non-shadowed regions in the color image, as a result, the shadows are reconstructed by correcting different region features with multi-scale gamma values. Experimental results show that the proposed method effectively reconstructs shadows in a single natural image.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.2
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• pp.23-28
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• 2004

In EIT, various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. In this paper, a SPSA approach is proposed for the solution of the EIT image reconstruction. Results of numerical experiments of EIT solved by the SPSA approach are presented and compared to that obtained by the modified Newton-Raphson(mNR) method.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.1
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• pp.45-52
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• 2016

This paper suggests a new method of finding regularization parameter for image restoration problems. Wiener filter requires priori information such that power spectrums of original image and noise. Constrained least squares restoration also requires knowledge of the noise level. If the prior information is not available, separate optimization functions for Tikhonov regularization parameter are suggested in the literature such as generalized cross validation and L-curve criterion. In this paper, self-regularization method that connects bias term of augmented linear system and smoothing term of Tikhonov regularization is introduced in the frequency domain and applied to the image restoration problems. Experimental results show the effectiveness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9B
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• pp.1588-1595
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• 2000

To restore image degraded by out-of-focus blur and additivie noise a regularized iterative restoration is used. In concentional method, regularization is usually applied to all over the image without considering the local characteristics of image. As a result, ringing artifacts appear in edge regions and the noise amplification is introduced in flat regions. To solve this problem we propose an adaptive regularization iterative restoration using directional regularization operator considering edges in four directions and the regularization operator with on direction for flat regions. We verified that the proposed method show better results in the suppression of the noise amplification in flat regions, and introduced less ringing artifacts in edge regions. As a result it showed visually better image and improved better ISNR further than the conventional methods.

• Journal of IKEEE
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• v.20 no.2
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• pp.152-162
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• 2016

Electrical resistivity tomography (ERT) is a technique to reconstruct the internal resistivity distribution using the measured voltages on the surface electrodes. ERT inverse problem suffers from ill-posedness nature, so regularization methods are used to mitigate ill-posedness. The reconstruction performance varies depending on the type of regularization method. In this paper, an interacting dual-mode regularization method is proposed with two different regularization methods, L1-norm regularization and total variation (TV) regularization, to achieve robust reconstruction performance. The interacting dual-mode regularization method selects the suitable regularization method and combines the regularization methods based on computed mode probabilities depending on the actual conditions. The proposed method is tested with numerical simulations and the results demonstrate an improved reconstruction performance.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.5 s.311
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• pp.68-79
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• 2006

Electrical capacitance tomography (ECT) is a non-invasive imaging reconstruction technique that aims at visualization of cross sectional permittivity distribution of dielectric object based on the measured capacitance. There are lots of iterative image reconstruction methods to accelerate convergence rate and enhance quality of reconstructed image, Among them iterative Landweber method is one of the widely used reconstruction algorithm in En. In this paper, modified generalized Landweber method is proposed to accelerate convergence rate. In doing so, acceleration term is considered to the generalized Landweber method with shaping matrix and an optimal step length is determined analytically. Extensive computer simulations are provided to illustrate the reconstruction performance of the proposed algorithm.

• The Journal of Korean Association of Computer Education
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• v.5 no.4
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• pp.43-52
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• 2002

A theory of binary wavelets which are performed over binary field has been recently proposed. Binary wavelet transform (BWT) of binary images can be used as an alternative to the real-valued wavelet transform of binary images in image processing applications such as compression, edge detection, and recognition. The BWT, however, requires large amount of computations for binary wavelet reconstruction since its operation is accomplished by matrix multiplication. In this paper, an efficient binary wavelet reconstruction method which utilizes filtering operation instead of matrix multiplication is presented. Experimental results show that the proposed algorithm can significantly reduce the computational complexity of the BWT. For the reconstruction of an $N{\times}N$ image, the proposed technique requires only $2MN^2$ multiplications and $2N(M-1)^2$ additions when the filter length M, while the BWT needs $2N^3$ multiplications and $2N(N-1)^2$ additions.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.457-460
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• 2000

본 연구는 HWT를 이용하여 인체상반신 영상에서 얼굴부위만을 분할하기 위한 알고리즘을 제안하였다. 제안한 알고리즘은 배경을 제거하기 위하여 인체 상반신영상을 2치화 영상으로 만들고, HWT를 적용하여 평균영상과 복원영상에서 고립점, 돌출부위, 경계중복점을 제거한 후 세선화과정을 통하여 경계검출을 수행한다. 다음으로 얼굴부위의 단순경계만을 갖는 마스크를 만들고, 원영상에 마스킹하여 효과적으로 얼굴부위만을 분할한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.261-263
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• 2014

최근 영화 <아바타>를 필두로 영화, 방송 등 영상매체에서 다양하게 3 차원 영상기술을 적용하고 있는 추세이다. 본 논문에서는 여러 가지 3 차원 영상 기술 중에서 가장 현실감이 높은 기술인 홀로그래피 (Holography)기술에 대하여 다루고자 한다. 우선 간략하게 홀로그래피 기술에 대하여 소개하고 홀로그램(Hologram)의 기록 및 복원 원리와 컴퓨터를 이용하여 홀로그래피 이미지를 만드는 컴퓨터 홀로그램 (Computer-generated hologram)에 대하여 기술하였으며, 범용 컴퓨터와 GPU(Graphics processing units)통해 컴퓨터 홀로그램 패턴을 기록 및 복원하는 실험을 진행해 보고, 시간 복잡도를 측정, 비교해 본다.