• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.163-168
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• 2011

In this paper, we proposed non-linear gamma curve algorithm for gamma correction. The previous non-linear gamma curve algorithm is generated by the least square polynomial using the Gauss-Jordan inverse matrix. However, the previous algorithm has some weak points. When calculating coefficients using inverse matrix of higher degree, occurred truncation errors. Also, only if input sample points are existed regular interval on 10-bit scale, the least square polynomial is accurately works. To compensate weak-points, we calculated accurate coefficients of polynomial using eigenvalue and orthogonal value of mat11x from singular value decomposition (SVD) and QR decomposition of vandemond matrix. Also, we used input data part segmentation, then we performed polynomial curve fitting and merged curve fitting results. When compared the previous method and proposed method using the mean square error (MSE) and the standard deviation (STD), the proposed segmented polynomial curve fitting is highly accuracy that MSE under the least significant bit (LSB) error range is approximately $10^{-9}$ and STD is about $10^{-5}$.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1170-1178
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• 2021

This paper proposed a versatile algorithm based on a dual-tree complex wavelet transform for intensifying the visual aspect of medical images. First, the decomposition of the input image into a high sub-band and low-sub-band image is done. Further, to improve the resolution of the resulting image, the high sub-band image is interpolated using Lanczos interpolation. Also, contrast enhancement is performed by singular value decomposition (SVD). Finally, the image reconstruction is achieved by using an inverse wavelet transform. Then, the Gaussian filter will improve the visual quality of the image. We have collected images from the hospital and the internet for quantitative and qualitative analysis. These images act as a reference image for comparing the effectiveness of the proposed algorithm with the existing state-of-the-art. We have divided the proposed algorithm into several stages: preprocessing, contrast enhancement, resolution enhancement, and visual quality enhancement. Both analyses show the proposed algorithm's effectiveness compared to existing methods.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.21-31
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• 2014

Singular value decomposition (SVD) has been widely used to identify unique features from a data set in various fields. However, a complex matrix calculation of SVD requires tremendous computation time. This paper improves the performance of a representative one-sided block Jacoby algorithm using a two-dimensional (2D) multi-core system. In addition, this paper explores an optimal multi-core system by varying the number of processing elements in the 2D multi-core system with the same 400MHz clock frequency and TSMC 28nm technology for each matrix-based one-sided block Jacoby algorithm ($128{\times}128$, $64{\times}64$, $32{\times}32$, $16{\times}16$). Moreover, this paper demonstrates the potential of the 2D multi-core system for the one-sided block Jacoby algorithm by comparing the performance of the multi-core system with a commercial high-performance graphics processing unit (GPU).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.338-344
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• 2017

In this paper, two-way amplify-and-forward relay methods are investigated where two terminals and one relay node are equipped with multiple antennas. In two-way relay channels, it is assumed that one terminal can eliminate its own self-interference but the other cannot. For this channel, we first maximize the sum-rate performance by employing an iterative gradient descent (GD) algorithm. Then, a simple singular value decomposition (SVD) based block triangularization is developed to null the self-interference. Simulation results show the proposed methods outperform the conventional schemes for various environments.

• Structural Engineering and Mechanics
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• v.14 no.2
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• pp.151-170
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• 2002

Moving force identification is a very important inverse problem in structural dynamics. Most of the identification methods are eventually converted to a linear algebraic equation set. Different ways to solve the equation set may lead to solutions with completely different levels of accuracy. Based on the measured bending moment responses of the bridge made in laboratory, this paper presented the time domain method (TDM) and frequency-time domain method (FTDM) for identifying the two moving wheel loads of a vehicle moving across a bridge. Directly calculating pseudo-inverse (PI) matrix and using the singular value decomposition (SVD) technique are adopted as means for solving the over-determined system equation in the TDM and FTDM. The effects of bridge and vehicle parameters on the TDM and FTDM are also investigated. Assessment results show that the SVD technique can effectively improve identification accuracy when using the TDM and FTDM, particularly in the case of the FTDM. This improved accuracy makes the TDM and FTDM more feasible and acceptable as methods for moving force identification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1708-1727
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• 2021

In the advent of the twenty-first century, human beings began to closely interact with technology. Today, technology is developing, and as a result, the world wide web (www) has a very important place on the Internet and the significant task is fulfilled by Web services. A lot of Web services are available on the Internet and, therefore, it is difficult to find matching Web services among the available Web services. The recommendation systems can help in fixing this problem. In this paper, our observation was based on the recommended method such as the collaborative filtering (CF) technique which faces some failure from the data sparsity and the cold-start problems. To overcome these problems, we first applied an ontology-based clustering and then the k-nearest neighbor (KNN) algorithm for each separate cluster group that effectively increased the data density using the past user interests. Then, user ratings were predicted based on the model-based approach, such as singular value decomposition (SVD) and the predictions used for the recommendation. The evaluation results showed that our proposed approach has a less prediction error rate with high accuracy after analyzing the existing recommendation methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.602-609
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• 2002

In this paper, we propose an robust invisible watermarking method using wavelet transform and singular value decomposition for the ownership protection. of images. For this method, after we decompose the original image in three level using wavelet transform, we use singular value decomposition based key depended watermark insertion method in the lowest band $LL_3.$ And we also watermark using DCT for extraction of watermark and verification of robustness. In the experiments, we found that it had a good quality and robustness in attack such as compression, image processing, geometric transformation and noises. Especially, we know that this method have very high extraction ratio against nose and JPEG compression. And Digimarc's method can not extract watermark in 80 percent compression ratio of JPEG, but the proposed method can extract well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1041-1043
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• 2016

This letter proposes a new blind fractionally spaced equalization (FSE). The conventional linear program (LP) FSE reduces the degree of freedom (DOF) by abandoning many equalization filter taps, which causes severe performance degradations. We use singular value decomposition (SVD) to obtain the signal subspace and to fully utilize all samples for performance improvement. The proposed scheme has similar performance with the nuclear norm minimization and has as low complexity as the LP equalizer.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.31-40
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• 2003

Most face recognition systems are based on 2D images and applied in many applications. However, it is difficult to recognize a face when the pose varies severely. Therefore, head pose estimation is an inevitable procedure to improve recognition rate when a face is not frontal. In this paper, we propose a novel head pose estimation algorithm for 3D face recognition. Given the 3D range image of an unknown face as an input, we automatically extract facial feature points based on the face curvature. We propose an Error Compensated Singular Value Decomposition (EC-SVD) method based on the extracted facial feature points. We obtain the initial rotation angle based on the SVD method, and perform a refinement procedure to compensate for remained errors. The proposed algorithm is performed by exploiting the extracted facial features in the normaized 3D face space. In addition, we propose a 3D nearest neighbor classifier in order to select face candidates for 3D face recognition. From simulation results, we proved the efficiency and validity of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9A
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• pp.1022-1030
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• 2004

The next generation cellular radio systems require high data rate transmission and large system capacity In order to meet these requirements, multiple antennas can be used at the base and mobile stations, forming MIMO(multiple-input, multiple-output) channels This paper considers a downlink MIMO system assuming a large number of base station antennas, a small number of mobile station antennas, and rich-scattering, quasi-stationary, and flat-fading channel environments When the channel state information is given at the base station in a single user system, a MIMO technique with SVD(singular value decomposition) and water-filling can achieve the maximal downlink channel capacity. In multi-user environments, however, SDMA(space division multiple acces) technique can be used to further increase the total channel capacity supported by the base station This paper proposes a MIMO SDMA technique which can transmit parallel data streams to each of multiple users. The proposed method. can achieve higher total channel capacity than SVD-based MIMO techniques or conventional SDMA using smart antennas.