• ETRI Journal
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• v.38 no.5
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• pp.858-867
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• 2016

A high dynamic range (HDR) video service is an upcoming issue in the broadcasting industry. For compatibility with legacy devices receiving a non-constant luminance (NCL) signal, new tools supporting an HDR video service are required. The current pre-processing chain of HDR video can produce color noise owing to the chroma component down-sampling process for video encoding. Although a luma adjustment method has been proposed to solve this problem, some disadvantages still remain. In this paper, we present an adaptive color noise reduction method for an NCL signal of an HDR video service. The proposed method adjusts the luma component of an NCL signal adaptively according to the information of the luma component from a constant luminance signal and the level of color saturation. Experiment results show that the color noise problem is resolved by applying our proposed method. In addition, the speed of the pre-processing is increased more than two-fold compared to a previous method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.128-135
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• 1996

In this paper, a digital signal processing method of AFC (automatic frequency control) is proposed for a home use VCR system. The proposed method has the ability of frequency tracking of a wide range. Implemented with digital circuits, the system is to be used in a digital video system and saves the cost of a hardware compared with a conventional analog automatic frequency control method using several PLL's in case of making home use VCR systems compatible with several TV systems.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.27-29
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• 2006

In this paper, we propose a new method of automatic white balance which is one of the image signal processing techniques. Our method is conceptually based on gray world assumption. However, while previous methods generate linear results as multiplying pixel values by a gain, our method generates non-linear results using the feature of B-Spline curves. The two merits of deriving non-linear results are preventing AWB failure from transforming strong color of high level into wrong color and well preserving original contrast of an input image.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.82-85
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• 2003

This paper proposes a preprocessing method for tracking aircraft's take-off and lading. The method uses accumulative difference image technique for segmenting the object from the background, and obtains the centroid of the object exactly using centroid method. Then the moving object is analyzed and represented with the information such as feature point, velocity, and distance. A simulation result reveals that the proposed algorithm has good performance in segmenting and tracking the aircraft.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.129-132
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• 2000

We propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process -control in various fields. First of all, in this method, initial values of DC motor are determined by the Ziegler-Nichols method. Finally, after studying the parameters of PID controller by input vector of multiple regression analysis, when we give new K, L, T values to multiple regression model, the optimized parameters of PID controller is found by multiple regression analysis program.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.293-299
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• 2004

This paper is about the extraction of basis function for ECG signal processing. In the first step, it is assumed that ECG signal consists of linearly mixed independent source signals. 12 channel ECG signals, which were sampled at 600sps, were used and the basis function, which can separate and detect source signals - QRS complex, P and T waves, - was found by applying the fast fixed point algorithm, which is one of learning algorithms in independent component analysis(ICA). The possibilities of significant point detection and classification of normal and abnormal ECG, using the basis function, were suggested. Finally, the proposed method showed that it could overcome the difficulty in separating specific frequency in ECG signal processing by wavelet transform. And, it was found that independent component analysis(ICA) could be applied to ECG signal processing for detection of significant points and classification of abnormal beats.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.3
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• pp.439-448
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• 1993

One of the main purposes of this paper is to propose a high resolution direction finding method performing particularly well under the circumstances such as correlated sensor noises, very closely spaced signal sources, and low signal-to-noise ratio(S/N), in array signal processing. Furthermore, the other is to demonstrate the superiority of the proposed method for each circumstance described above, in comparison with the methods previously developed.

• Journal of Sensor Science and Technology
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• v.23 no.1
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• pp.1-6
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• 2014

In many medical image devices, dc noise often prevents normal diagnosis. In wireless capsule endoscopy systems, multipath fading through indoor wireless links induces inter-symbol interference (ISI) and indoor electric devices generate impulsive noise in the received signal. Moreover, dc noise, ISI, and impulsive noise are also found in optical fiber communication that can be used in remote medical diagnosis. In this paper, a blind signal processing method based on the biased probability density functions of constant modulus error that is robust to those problems that can cause error propagation in decision feedback (DF) methods is presented. Based on this property of robustness to error propagation, a DF version of the method is proposed. In the simulation for the impulse response of optical fiber channels having slowly varying dc noise and impulsive noise, the proposed DF method yields a performance enhancement of approximately 10 dB in mean squared error over its linear counterpart.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.495-498
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• 2004

In the sound insulation measurements, the influence of background (extraneous) noise is often serious problem and how to reduce its effect and to improve the signal-to-noise(S/N) ratio is an important theme. As the background noise, such extraneous noises as road traffic noise and machine noise often disturb the measurement. In laboratory measurements on specimens with high sound insulation performances, even the internal noise of the measurement system can become a problem. To improve the signal-to-noise ratio and to improve the measurement accuracy, various kinds of digital signal processing techniques can be applied. In this paper, four kinds of digital signal processing techniques are applied and their effectiveness is examined by a simple sound insulation measurement.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.84-89
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• 2014

Data-driven method for fault diagnostics system often use machine learning technique. To use such technique proper signal processing should be implemented such as time synchronous averaging (TSA) for ball bearing systems. However, for journal bearing diagnostics systems not much has been researched, and yet a proper signal processing method has not been studied. Therefore, in this research an optimal datum unit for a reliable journal bearing diagnostics system along with angular resampling process is being suggested. Before extracting time and frequency domain features, angular resampling is applied to each cycle of vibration data. As to preserve the characteristics of vibration signal, averaging method is replaced by finding the optimal datum unit which strengthens statistical characteristics of vibration signal. Then 20 features were extracted for various cases, and those features are being evaluated by two criteria, separability and classification accuracy.