• Journal of the Institute of Convergence Signal Processing
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• v.14 no.1
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• pp.33-38
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• 2013

In this paper, we propose an algorithm to track multi-small targets in infrared image sequences in case of dissipation or creation of targets by using the background estimation filter, Kahnan filter and mean shift algorithm. We detect target candidates in a still image by subtracting an original image from an background estimation image, and we track multi-targets by using Kahnan filter and target selection. At last, we adjust specific position of targets by using mean shift algorithm In the experiments, we compare the performance of each background estimation filters, and verified that proposed algorithm exhibits better performance compared to classic methods.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.1
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• pp.6-12
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• 2013

Mammography is the most common technique for the early detection of breast cancer. To diagnose correctly and treat of breast cancer efficiently, many image enhancement methods have been developed. This paper presents a nonlinear image enhancement method for the enhancement of digital mammogram. The proposed method is composed of a nonlinear function for brightness improvement and a nonlinear filter for contrast enhancement. The nonlinear function improves the brightness of dark area and extends the dynamic range of bright area, and the nonlinear filter efficiently enhances the specific regions and objects of the mammogram. The final enhanced image was obtained by combining the processed image with the nonlinear function and the filtered image with the nonlinear filter. The proposed nonlinear image enhancement method was confirmed the enhanced performance comparing with other existing methods.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.73-77
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• 2007

In this paper, we propose a VLSI architecture of an LMS filter based on a Cyclo-static scheduler for fast computation of LMS filteing algorithm which is widely used in adptive filtering area. This process is composed of two steps: scheduling and circuit synthesis. The scheduling step accepts a fully specified flow graph(FSFG) as an input, and generates an optimal Cyclo-static schedule in the sense of the sampling rate, the number of processors, and the input-output delay. Then the generated schedule is transformed so that the number of communication edges between the processors. The circuit synthesis part translates the modified schedule into a complete circuit diagram by performing resource allocations. The VLSI layout generation can be performed easily by an existing silicon compiler.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.248-251
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• 1999

We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-1, we may compute the updated estimate of this vector at i(oration n upon the arrival of new data. The RLS algorithm may be viewed as a special case of the Kalman filter. Indeed this special relationship between the RLS algorithm and the Kalman filter is considered. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. The resulting rate of convergence is therefore typically an order of magnitude faster than the simple LMS algorithm. This improvement in performance, however, Is achieved at the expensive of a large increase in computational complexity.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.209-212
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• 2003

In this paper, we have analyzed a multiwavelet filter bank architecture which have several bases. The filter bank composed of multiwavelets bases is matrix-valued. Multiwavelets offer simultaneous orthogonality, symmetry, and short support, which is not possible for the scalar wavelet system, hence multiwavelet system can obtain excellent performance in signal analysis and compress. Also the multiwavelet differs from the scalar wavelet system in requiring two or more input streams to the multiwavelet filter bank. In this paper, we describe methods for obtaining such a input stream and how apply the actual data.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.178-185
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• 2021

Three-dimensional high-resolution magnetic resonance imaging (MRI) provides fine-level anatomical information for disease diagnosis. However, there is a limitation in obtaining high resolution due to the long scan time for wide spatial coverage. Therefore, in order to obtain a clear high-resolution(HR) image in a wide spatial coverage, a super-resolution technology that converts a low-resolution(LR) MRI image into a high-resolution is required. In this paper, we propose a super-resolution technique through filter learning based on information on the surrounding gradient information in 3D space from 3D MRI images. In the learning step, the gradient features of each voxel are computed through eigen-decomposition from 3D patch. Based on these features, we get the learned filters that minimize the difference of intensity between pairs of LR and HR images for similar features. In test step, the gradient feature of the patch is obtained for each voxel, and the filter is applied by selecting a filter corresponding to the feature closest to it. As a result of learning 100 T1 brain MRI images of HCP which is publicly opened, we showed that the performance improved by up to about 11% compared to the traditional interpolation method.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.4_2
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• pp.443-451
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• 2021

It is essential to examine and analyze the power output and load responses together using real-world turbulent wind speeds. In this paper, the power controller and the drive train damper are simultaneously considered using the NREL 5MW wind turbine model, and the damage equivalent load(DEL) of the low speed shaft torque and power output responses according to the natural frequency of the second order low pass filter are simultaneously investigated. Numerical testing is carried out above rated wind speed using commercially available Bladed software. From the viewpoints of DEL reduction of the drive train shaft torque and power output responses, it is shown that the natural frequency of the low pass filter is appropriately about 6 to 10rad/s. And the reduction ratio of the DEL of the low-speed shaft torque decreases as the wind speed becomes higher, and it is confirmed that the reduction ratio is limited to about 20% at high wind speeds.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.39-42
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• 1999

Adaptive array is using the array of antenna elements spatially and its output is the sum of each antenna elements output signal which is multiplied by the controlled weight coefficients corresponding to each elements. In this paper, for the BPSK and BFSK signals with S/I=2, S/N=10 is applied to the linear array antenna using the LMS & the Kalman filter algorithm. For the 4 elements equidistance linear array antenna system LMS and Kalman filter algorithm was used as the adaptive instruction principles and the application results to the constant amplitude envelope signals such as BPSK or BFSK can be seen that the computer simulation results are very fast in the convergence characteristics of directional patterns and the signal following characteristics.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.262-264
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• 2005

We propose a filter design method to suppress the effect of gyroscope mixed random errors at INS system level. It is based on the result that mixed random errors can be represented by a single equivalent ARMA model. At first step, the time difference of equivalent ARMA process is performed, which consider the characteristic of indirect feedback Kalman filter used in INS filter. Next, a state space conversion of time differenced ARMA model is achieved. If the order of AR is greater than that of MA, the controllable or observable canonical form is used. Otherwise, we introduce the state equation of which the state variable is composed of the ARMA model output and several step ahead predicts of that. At final step, a complete form state equation is presented. The simulation results shows that the proposed method gives less transient error and better convergence compared to the conventional filter which assume the mixed random errors as white noise.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1435-1438
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• 2005

In hands-free telephone systems, the received speech signal is fed back to the microphone and constitutes the so-called echo. To cancel the effect of this time-varying echo path, it is necessary to device an adaptive filter between the receiving and the transmitting ends. For a typical FIR realization, the length of the fullband adaptive filter results in high computational complexity and low convergence rate. Consequently, subband adaptive filtering schemes have been proposed to improve the performance. In this work, we use deterministic approach to analyze the relationship between fullband and subband adaptive filtering structures. With block adaptive filtering structure as an intermediate stage, the analysis is divided into two parts. First, to avoid aliasing, it is found that the matrix of block adaptive filters is in the form of pseudocirculant, and the elements of this matrix are the polyphase components of the fullband adaptive filter. Second, to transmit the near-end voice signal faithfully, the analysis and the synthesis filter banks in the subband adaptive filtering structure must form a perfect reconstruction pair. Using polyphase representation, the relationship between the block and the subband adaptive filters is derived.