• 제목/요약/키워드: rank minimization

검색결과 10건 처리시간 0.036초

낮은 계수 행렬의 Compressed Sensing 복원 기법 (Compressed Sensing of Low-Rank Matrices: A Brief Survey on Efficient Algorithms)

  • 이기륭;예종철
    • 대한전자공학회논문지SP
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    • 제46권5호
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    • pp.15-24
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    • 2009
  • Compressed sensing은 소수의 선형 관측으로부터 sparse 신호를 복원하는 문제를 언급하고 있다. 최근 벡터 경우에서의 성공적인 연구 결과가 행렬의 경우로 확장되었다. Low-rank 행렬의 compressed sensing은 ill-posed inverse problem을 low-rank 정보를 이용하여 해결한다. 본 문제는 rank 최소화 혹은 low-rank 근사의 형태로 나타내질 수 있다. 본 논문에서는 최근 제안된 여러 가지 효율적인 알고리즘에 대한 survey를 제공한다.

다중 잡음 제거 영상을 이용한 Non-convex Low Rank 최소화 기법 기반 영상 잡음 제거 기법 (Image Denoising via Non-convex Low Rank Minimization Using Multi-denoised image)

  • 유준상;김종옥
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송∙미디어공학회 2018년도 하계학술대회
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    • pp.20-21
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    • 2018
  • 행렬의 rank 최소화 기법은 영상 잡음 제거, 행렬 완성(completion), low rank 행렬 복원 등 다양한 영상처리 분야에서 효과적으로 이용되어 왔다. 특히 nuclear norm 을 이용한 low rank 최소화 기법은 convex optimization 을 통하여 대상 행렬의 특이값(singular value)을 thresholding 함으로써 간단하게 low rank 행렬을 얻을 수 있다. 하지만, nuclear norm 을 이용한 low rank 최소화 방법은 행렬의 rank 값을 정확하게 근사하지 못하기 때문에 잡음 제거가 효과적으로 이루어지지 못한다. 본 논문에서는 영상의 잡음을 제거 하기 위해 다중 잡음 제거 영상을 이용하여 유사도가 높은 유사 패치 행렬을 구성하고, 유사 패치 행렬의 rank 를 non-convex function 을 이용하여 최소화시키는 방법을 통해 잡음을 제거하는 방법을 제안한다.

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Truncated Nuclear Norm 최소화를 이용한 HDR 영상 합성 (HDR Image Synthesis Using Truncated Nuclear Norm Minimization)

  • 이철
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2015년도 추계학술대회
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    • pp.108-109
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    • 2015
  • 본 논문은 low-rank 행렬의 truncated nuclear norm 최소화를 이용한 HDR (high dynamic range) 영상 합성 기법을 제안한다. 제안하는 기법에서는 기존의 LDR (low dynamic range) 영상에서 얻은 밝기의 선형 관계에 기반하여 HDR 합성을 low-rank 행렬 완성 문제로 변환한 후, ALM (augmented Lagrange multiplier) 기법을 이용하여 효율적으로 최적의 해를 구한다. 컴퓨터 모의실험을 통해 제안하는 기법이 기존 기법에 비해서 낮은 계산 복잡도를 보이면서도 더 높은 품질의 HDR 영상을 합성하는 것을 확인한다.

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쌍대반응표면최적화를 위한 가중평균제곱오차 최소화법: 공정능력지수 기반의 가중치 결정 (Weighted Mean Squared Error Minimization Approach to Dual Response Surface Optimization: A Process Capability Indices-Based Weighting Procedure)

  • 정인준
    • 품질경영학회지
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    • 제42권4호
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    • pp.685-700
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    • 2014
  • Purpose: The purpose of this paper is to develop a systematic weighting procedure based on process capability indices method applying weighted mean squared error minimization (WMSE) approach to dual response surface optimization. Methods: The proposed procedure consists of 5 steps. Step 1 is to prepare the alternative vectors. Step 2 is to rank the vectors based on process capability indices in a pairwise manner. Step 3 is to transform the pairwise rankings into the inequalities between the corresponding WMSE values. Step 4 is to obtain the weight value by calculating the inequalities. Or, step 5 is to obtain the weight value by minimizing the total violation amount, in case there is no weight value in step 4. Results: The typical 4 process capability indices, namely, $C_p$, $C_{pk}$, $C_{pm}$, $C_{pmk}$ are utilized for the proposed procedure. Conclusion: The proposed procedure can provide a weight value in WMSE based on the objective quality performance criteria, not on the decision maker's subjective judgments or experiences.

STFT 기반 영상분석을 이용한 효과적인 잡음제거 알고리즘 (Effective Noise Reduction using STFT-based Content Analysis)

  • 백승인;정수웅;최종수;이상근
    • 전자공학회논문지
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    • 제52권4호
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    • pp.145-155
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    • 2015
  • 디지털 영상 처리 분야에서 잡음 제거는 활발히 연구되어오고 있으며, 최근에는 블록 기반의 잡음 제거 알고리즘이 널리 사용되고 있다. 저계수행렬 근사 기반의 잡음 제거 알고리즘은 WNNM(Weighted Nuclear Norm Minimization)과 블록 기반의 잡음 제거 방법을 적용하여 잡음 제거 방법에 대한 잠재력을 입증했다. 그러나 저계수행렬 근사 기반의 잡음 제거 알고리즘은 영상복원 과정에서 의도치 않은 아티팩트를 발생시킨다. 본 논문에서는 STFT(Short Time Fourier Transform)을 이용해 영상을 분석하여 기존 알고리즘에서 발생하는 아티팩트를 적응적으로 최소화시키는 방법을 제안한다. 성능을 확인하기 위해 다양한 잡음정도를 포함하는 영상에서 실험하였으며, 비교를 통해 제안된 방법이 기존의 잡음 제거 알고리즘보다 효과적으로 잡음을 제거하는 것을 확인했다.

Image Denoising for Metal MRI Exploiting Sparsity and Low Rank Priors

  • Choi, Sangcheon;Park, Jun-Sik;Kim, Hahnsung;Park, Jaeseok
    • Investigative Magnetic Resonance Imaging
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    • 제20권4호
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    • pp.215-223
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    • 2016
  • Purpose: The management of metal-induced field inhomogeneities is one of the major concerns of distortion-free magnetic resonance images near metallic implants. The recently proposed method called "Slice Encoding for Metal Artifact Correction (SEMAC)" is an effective spin echo pulse sequence of magnetic resonance imaging (MRI) near metallic implants. However, as SEMAC uses the noisy resolved data elements, SEMAC images can have a major problem for improving the signal-to-noise ratio (SNR) without compromising the correction of metal artifacts. To address that issue, this paper presents a novel reconstruction technique for providing an improvement of the SNR in SEMAC images without sacrificing the correction of metal artifacts. Materials and Methods: Low-rank approximation in each coil image is first performed to suppress the noise in the slice direction, because the signal is highly correlated between SEMAC-encoded slices. Secondly, SEMAC images are reconstructed by the best linear unbiased estimator (BLUE), also known as Gauss-Markov or weighted least squares. Noise levels and correlation in the receiver channels are considered for the sake of SNR optimization. To this end, since distorted excitation profiles are sparse, $l_1$ minimization performs well in recovering the sparse distorted excitation profiles and the sparse modeling of our approach offers excellent correction of metal-induced distortions. Results: Three images reconstructed using SEMAC, SEMAC with the conventional two-step noise reduction, and the proposed image denoising for metal MRI exploiting sparsity and low rank approximation algorithm were compared. The proposed algorithm outperformed two methods and produced 119% SNR better than SEMAC and 89% SNR better than SEMAC with the conventional two-step noise reduction. Conclusion: We successfully demonstrated that the proposed, novel algorithm for SEMAC, if compared with conventional de-noising methods, substantially improves SNR and reduces artifacts.

특이값 분해를 이용한 블라인드 부분 간격 등화기 (Fractionally Spaced Blind Equalization Using Singular Value Decomposition)

  • 김금비;이정원;남해운;박대영
    • 한국통신학회논문지
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    • 제41권9호
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    • pp.1041-1043
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    • 2016
  • 이 논문은 새로운 블라인드 부분 간격 등화기를 제안한다. 기존의 선형 계획법을 이용한 등화기는 등화기 필터 탭의 자유도를 강제로 줄였기 때문에 성능이 저하된다. 제안 방법은 특이값 분해를 통해 신호 공간을 구해 표본을 최대한 사용하여 등화기 성능을 향상시킨다. 제안 방법은 핵 노름을 이용한 등화기와 성능은 비슷하면서도, 기존 선형 계획법을 이용한 등화기와 비슷한 낮은 복잡도를 갖는다.

전라남도 식품업체의 비용 효율성 분석 (The Cost Efficiency Analysis of JeollaNamdo Food Industry)

  • 경성림;나주몽;장석주;임창욱
    • 품질경영학회지
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    • 제43권4호
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    • pp.533-544
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    • 2015
  • Purpose: The purpose of this study is to analyze the cost efficiency of food industry in JeollaNamdo. And this study is focused on the correlation between the economic efficiency of food industry and its cost efficiency, based on the analysis of 372 food companies' data in JeollaNamdo in 2012. Methods: DEA cost minimization is the measurement of the cost efficiency of JeollaNamdo food industry in 2012. In this study, the CCR and BBC models have been employed to analyze the decomposing cost efficiency-technical efficiency, allocative efficiency, and scale efficiency respectively. And the Spearman rank correlation and Wilcoxon signed rank test also have been employed to check the correlation and difference between the ranking orders based on the efficiency scores respectively. Results: For the CCR model, mean cost efficiency was found to be 0.084(0.54 for allocative efficiency and 0.19 for technical efficiency). For the BCC model, mean cost efficiency was found to be 0.252(0.453 for allocative efficiency and 0.564 for technical efficiency). Average scale efficiency was found to be 0.38. In analyzing the results, this study argues that the optimal way to improve cost efficiency is by reducing inputs proportionally and changing their combination. Conclusion: The efficiency scores of the two models show high correlation, whereas, the differences between them are also found to be significant. Hence, it should be cautious to select a suitable model when we do the research.

복합재료판 구조물의 고유진동수 위상최적화에 관한 연구 (Study on Topology Optimization for Eigenfrequency of Plates with Composite Materials)

  • 김화일;윤혁기;한경민
    • 한국소음진동공학회논문집
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    • 제19권12호
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    • pp.1356-1363
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    • 2009
  • The aim of this research is to construct eigenfrequency optimization codes for plates with Arbitrary Rank Microstructures. From among noise factors, resonance sound is main reason for floor's solid noise. But, Resonance-elusion design codes are not fixed so far. Besides, The prediction of composite material's capability and an resonance elusion by controlling natural frequency of plate depend on designer's experiences. In this paper, First, using computer program with arbitrary rank microstructure, variation on composite material properties is studied, and then natural frequency control is performed by plate topology optimization method. The results of this study are as followed. 1) Programs that calculate material properties along it's microstructure composition and control natural frequency on composite material plate are coded by Homogenization and Topology Optimization method. and it is examined by example problem. 2) Equivalent material properties, calculated by program, are examined for natural frequency. In this paper, Suggested programs are coded using $Matlab^{TM}$, Feapmax and Feap Library with Homogenization and Topology Optimization method. and Adequacy of them is reviewed by performing the maximization or minimization of natural frequency for plates with isotropic or anisotropic materials. Since the programs has been designed for widely use. If the mechanism between composite material and other structural member is identified, extension application may be possible in field of structure maintenance, reinforcement etc. through application of composite material.

확률적 타부 탐색 전략을 이용한 새로운 함수 최적화 방법에 관한 연구 (A Study on a New Function Optimization Method Using Probabilistic Tabu Search Strategy)

  • 김형수;황기현;박준호
    • 대한전기학회논문지:시스템및제어부문D
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    • 제50권11호
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    • pp.532-540
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    • 2001
  • In this paper, we propose a probabilistic tabu search strategy for function optimization. It is composed of two procedures, one is Basic search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify search region. In basic search procedure, we use Belief space and Near region to create neighbors. Belief space is made of high-rank neighbors to effectively restrict searching space, so it can improve searching time and local or global searching capability. When a solution is converged in a local area, Restarting procedure works to search other regions. In this time, we use Probabilistic Tabu Strategy(PTS) to adjust parameters such as a reducing rate, initial searching region etc., which makes enhance the performance of searching ability in various problems. In order to show the usefulness of the proposed method, the PTS is applied to the minimization problems such as De Jong functions, Ackley function, and Griewank functions etc., the results are compared with those of GA or EP.

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