• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.15-24
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• 2009

Compressed sensing addresses the recovery of a sparse vector from its few linear measurements. Recently, the success for the vector case has been extended to the matrix case. Compressed sensing of low-rank matrices solves the ill-posed inverse problem with fie low-rank prior. The problem can be formulated as either the rank minimization or the low-rank approximation. In this paper, we survey recently proposed efficient algorithms to solve these two formulations.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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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.

• Journal of Hydrogen and New Energy
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• v.26 no.6
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• pp.567-580
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• 2015

In order to select an optimum gasifier for specific low rank coal, evaluation elements were studied by analyzing characteristics of low rank coal compared with those of high rank coal and the effects of each gasifier type in accordance with the characteristics. And syngas composition calculation model was made on the basis of thermochemical equilibrium to quantify some of the evaluation elements. And then the suitable gasifier was selected for a kind of Indonesian low rank coal through this syngas composition calculation model and the evaluation elements of selecting gasifier.

• 한국연소학회:학술대회논문집
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• 2013.06a
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• pp.129-132
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• 2013

The low rank coal combustion and biomass-coal co-firing characteristics were reviewed on this study for the power plant construction. The importance of using low rank coal(LRC) for power plant is increasing gradually due to power generation economy and biomass co-firing is also concentrated as power source because it has carbon neutral characteristics to reduce green-house effect. The combustion characteristics of low rank coal and biomass for a 310MW coal firing power plant and a 100MW biomass and coal co-firing power plant were studied to apply into actual power plant design and optimized the furnace and burner design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3745-3761
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• 2020

Low-rank representation methods already achieve many applications in the image reconstruction. However, for high-gradient image patches with rich texture details and strong edge information, it is difficult to find sufficient similar patches. Existing low-rank representation methods usually destroy image critical details and fail to preserve edge structure. In order to promote the performance, a new representation-based image super-resolution reconstruction method is proposed, which combines gradient domain guided image filter with the structure-constrained low-rank representation so as to enhance image details as well as reveal the intrinsic structure of an input image. Firstly, we extract the gradient domain guided filter of each atom in high resolution dictionary in order to acquire high-frequency prior information. Secondly, this prior information is taken as a structure constraint and introduced into the low-rank representation framework to develop a new model so as to maintain the edges of reconstructed image. Thirdly, the approximate optimal solution of the model is solved through alternating direction method of multipliers. After that, experiments are performed and results show that the proposed algorithm has higher performances than conventional state-of-the-art algorithms in both quantitative and qualitative aspects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1317-1322
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• 2021

Nonlocal similarity of natural images leads to the fact that a patch matrix whose columns are similar patches of the reference patch has a low rank. Images corrupted by additive white Gaussian noises (AWGN) make their patch matrices to have a higher rank. The noise in the image can be reduced by obtaining low rank approximation of the patch matrices. In this paper, an image denoising algorithm is proposed, which first constructs the patch matrices by combining the similar patches of each reference patch, which is a part of the noisy image. For each patch matrix, the proposed algorithm calculates its low rank approximate, and then recovers the original image by aggregating the low rank estimates. The simulation results using widely accepted test images show that the proposed denoising algorithm outperforms four recent methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1296-1302
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• 2007

In this paper, we propose joint estimation methods of carrier offset and channel estimation for MB-OFDM system with low complexity. The proposed methods estimate the channel by using low-rank LMMSE channel estimation which reduces the system complexity by applying the optimal number of rank to evaluate the frequency offset and additionally using the simple algorithm using the auto-correlation property of the estimated channel. We simulate the proposed algorithms under the IEEE 802.15 TG3a UWB channel model.

• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.494-502
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• 2002

In this paper, the Low Rank Approximation (LRA) method to suppress the interference of signals from temporal fluctuations is applied. The reverberation signals and temporally fluctuating signals are separated from the measured data using the Ink. The Singular value decomposition (SVD) method is applied to extract the low rank and the temporally stable reverberation was extracted using the LRA. The reverberation suppression is performed on the LRA residual value obtained by removing the approximate reverberation signals. In overall, the method can be applied to the suppression of reververation in active sonar system as well as to the modeling of reverberation.

• Journal of Hydrogen and New Energy
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• v.30 no.2
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• pp.178-187
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• 2019

Due to the increasing demand of high rank coal, the use of low rank coal, which has economically advantage, is rising in various industries using carbonaceous solid fuels. In addition, the severe disaster of global warming caused by greenhouse gas emissions is becoming more serious. The Republic of Korea set a goal to reduce greenhouse gas emissions by supporting the use of biomass from the Paris International Climate Change Conference and the 8th Basic Plan for Electricity Supply and Demand. In line with these worldwide trends, this paper focuses on investigating the combustibility of high rank coal Carboone, low rank coal Adaro from Indonesia, Baganuur from Mongolia and, In biomass, wood pellet and herbaceous type Kenaf were simulated as kinetic reactivity model. The accuracy of the pore development model were compared with experimental result and analyzed using carbon conversion and tau with grain model, random pore model, and flexibility-enhanced random pore model. In row lank coal and biomass, FERPM is well-matched kinetic model than GM and RPM to using numerical simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4510-4526
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• 2017

Most available methods of facial gender recognition work well under a constrained situation, but the performances of these methods have decreased significantly when they are implemented under unconstrained environments. In this paper, a method via low-rank and collaborative representation is proposed for facial gender recognition in the wild. Firstly, the low-rank decomposition is applied to the face image to minimize the negative effect caused by various corruptions and dynamical illuminations in an unconstrained environment. And, we employ the collaborative representation to be as the classifier, which using the much weaker $l_2-norm$ sparsity constraint to achieve similar classification results but with significantly lower complexity. The proposed method combines the low-rank and collaborative representation to an organic whole to solve the task of facial gender recognition under unconstrained environments. Extensive experiments on three benchmarks including AR, CAS-PERL and YouTube are conducted to show the effectiveness of the proposed method. Compared with several state-of-the-art algorithms, our method has overwhelming superiority in the aspects of accuracy and robustness.