• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.372-378
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• 2014

Noise in biomedical X-ray image degrades the quality so that it might causes to decrease the accuracy of diagnosis. Especially the noise reduction techniques is quite essential for low-dose biomedical X-ray images obtained from low radiation power in order to protect patients, because their noise level is usually high to well discriminate objects. This paper proposes an efficient method to remove the noise in low-dose X-ray images while preserving the edges with diverse resolutions. In the proposed method, a noisy image is at first decomposed into several images with different resolutions in pyramidal representation, then the stable map of edge confidence is obtained from each of analyzed image using a fuzzy logic-based edge detector. This map is used to adaptively determine the parameter for guided filters, which eliminate the noise while preserving edges in the corresponding image. The filtered images in the pyramid are extended and synthesized into a resulted image using interpolation technique. The superiority of proposed method compared to the median, bilateral, and guided filters has been experimentally shown in terms of noise removal and edge preserving properties.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.385-390
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• 2006

This paper examines the sampling and jitter specifications and considerations for Global Navigation Satellite Systems (GNSS) software receivers. Software radio (SWR) technologies are being used in the implementation of communication receivers in general and GNSS receivers in particular. With the advent of new GPS signals, and a range of new Galileo and GLONASS signals soon becoming available, GNSS is an application where SWR and software-defined radio (SDR) are likely to have an impact. The sampling process is critical for SWR receivers, where it occurs as close to the antenna as possible. One way to achieve this is by BandPass Sampling (BPS), which is an undersampling technique that exploits aliasing to perform downconversion. BPS enables removal of the IF stage in the radio receiver. The sampling frequency is a very important factor since it influences both receiver performance and implementation efficiency. However, the design of BPS can result in degradation of Signal-to-Noise Ratio (SNR) due to the out-of-band noise being aliased. Important to the specification of both the ADC and its clocking Phase- Locked Loop (PLL) is jitter. Contributing to the system jitter are the aperture jitter of the sample-and-hold switch at the input of ADC and the sampling-clock jitter. Aperture jitter effects have usually been modeled as additive noise, based on a sinusoidal input signal, and limits the achievable Signal-to-Noise Ratio (SNR). Jitter in the sampled signal has several sources: phase noise in the Voltage-Controlled Oscillator (VCO) within the sampling PLL, jitter introduced by variations in the period of the frequency divider used in the sampling PLL and cross-talk from the lock line running parallel to signal lines. Jitter in the sampling process directly acts to degrade the noise floor and selectivity of receiver. Choosing an appropriate VCO for a SWR system is not as simple as finding one with right oscillator frequency. Similarly, it is important to specify the right jitter performance for the ADC. In this paper, the allowable sampling frequencies are calculated and analyzed for the multiple frequency BPS software radio GNSS receivers. The SNR degradation due to jitter in a BPSK system is calculated and required jitter standard deviation allowable for each GNSS band of interest is evaluated. Furthermore, in this paper we have investigated the sources of jitter and a basic jitter budget is calculated that could assist in the design of multiple frequency SWR GNSS receivers. We examine different ADCs and PLLs available in the market and compare known performance with the calculated budget. The results obtained are therefore directly applicable to SWR GNSS receiver design.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.

• Smart Media Journal
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• v.2 no.2
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• pp.33-38
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• 2013

In this paper, we investigated baseline estimation methods for remove background noise using Raman spectra from acute alcohol liver injury and acute ethanol-induced chronic liver fibrosis. Far the baseline estimation, we applied first derivative, linear programming and rolling ball method. Optimal input parameter of each method were determined by the training rate of MAP (maximum a posteriori probability) classifier. According to the experimental results, classification results baseline estimation with the rolling ball algorithm gave about 89.4%, which is very promising results for classification of acute alcohol liver injury and acute ethanol-induced chronic liver fibrosis. From these results, to determined the appropriate methods and parameters of baseline estimation impact on classification performance was confirmed.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.482-485
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• 2004

We fabricated a hybrid bulk/fully depleted silicon on insulator (FDSOI) complementary metal oxide semiconductor (CMOS) active pixel image sensor. The active pixel is comprised of reset and source follower transistors on the SOI seed wafer, while the pinned photodiode and readout gate and floating diffusion are fabricated on the SOI handle wafer after the removal of the buried oxide. The source of dark current is eliminated by hybrid bulk/FDSOI pixel structure between localized oxidation of silicon (LOCOS) and photodiode(PD). By using the low noise hybrid pixel structure, dark currents qm be suppressed significantly. The pinned photodiode can also be optimized for quantum efficiency and reduce the noise of dark current. The spectral response of the pinned photodiode on the SOI handle wafer is very flat between 400 nm and 700 nm and the dark current that is higher than desired is about 10 nA/cm2 at a $V_{DD}$ of 2 V.

• Advances in aircraft and spacecraft science
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• v.7 no.5
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• pp.425-440
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• 2020

The work presented herein is a numerical investigation of the flow field inside a resonant igniter, with the aim of predicting the performances in terms of cavity temperature and noise spectrum. A resonance ignition system represens an attractive solution for the ignition of liquid rocket engines in space missions which require multiple engine re-ignitions, like for example debris removal. Furthermore, the current trend in avoiding toxic propellants leads to the adoption of green propellant which does not show hypergolic properties and so the presence of a reliable ignition system becomes fundamental. Resonant igniters are attractive for in-space thrusters due to the low weight and the absence of an electric power source. However, their performances are strongly influenced by several geometrical and environmental parameters. This motivates the study proposed in this work in which the flow field inside a resonant igniter is numerically investigated. The unsteady compressible Reynolds Averaged Navier-Stokes equations are solved by means of a finite volume scheme and the effects of several wall boundary conditions are investigated (adiabatic, isothermal, radiating). The results are compared with some available experimental data in terms of cavity temperature and noise spectrum.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.325-328
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• 2013

본 논문에서는 ToF(Time-of-Flight) 카메라의 거리 잡음을 제거하는 방법으로 거리와 진폭에 따른 거리 잡음 모델링을 이용한 적응적인 SUSAN(Smallest Univalue Segment Assimilating Nucleus) 필터를 제안한다. ToF 카메라의 거리 잡음 제거를 위해서 기존에 제안된 여러 가지 방법들은 거리 잡음의 특성을 고려하지 않거나 진폭에 따른 거리 잡음의 특성만을 고려하였다. 하지만 실제 ToF 카메라의 거리 영상에 포함되는 거리 잡음은 진폭과 거리에 따라서 변화하기 때문에 거리와 진폭을 모두 고려한 거리 잡음 모델링이 필요하다. 따라서 제안하는 방법은 우선 거리와 진폭의 변화에 따른 ToF 카메라의 거리 잡음 특성을 모델링 한다. 이후 제안하는 방법은 생성된 거리 잡음 모델에 의해 인자가 결정되는 적응적 SUSAN 필터를 이용하여 ToF 카메라의 거리 영상의 잡음을 제거한다. 실험 결과 제안하는 방법은 기존의 ToF 거리 영상의 거리 잡음제거 방법에 비해 보다 효과적으로 거리 영상의 잡음을 제거하면서 디테일을 잘 보존하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.11
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• pp.1645-1654
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• 1993

Unlike a noise removal recursive temporal filter, this paper presents a temporal filter which improves visual quality and data compression efficiency. In general, for the temporal band-limitation, temporal aliasing should be considered. Since most of a video signal has temporally aliased components, it is desirable to consider them. From a signal processing point of view, it is impossible to realize the filtering not afeced by the aliasings. However, in this paper, efficient filtering with de-aliasing characteristics is proposed. Considering the location of a video signal, temporal filtering can be accomplished by the spatial filtering along the motion vector trajectory (Motion Adaptive Spatial Filter). This filtered result dose not include the aliasings. Besides the efficient band-limitation, temporal noise is also reduced. For the evaluation of the MASF, its realization and filtering characteristics will be discussed in ditail.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5073-5086
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• 2015

The rock fracture detection by image analysis is significant for fracture measurement and assessment engineering. The paper proposes a novel image segmentation algorithm for the centerline tracing of a rock fracture based on Hessian Matrix at Multi-scales and Steger algorithm. A traditional fracture detection method, which does edge detection first, then makes image binarization, and finally performs noise removal and fracture gap linking, is difficult for images of rough rock surfaces. To overcome the problem, the new algorithm extracts the centerlines directly from a gray level image. It includes three steps: (1) Hessian Matrix and Frangi filter are adopted to enhance the curvilinear structures, then after image binarization, the spurious-fractures and noise are removed by synthesizing the area, circularity and rectangularity; (2) On the binary image, Steger algorithm is used to detect fracture centerline points, then the centerline points or segments are linked according to the gap distance and the angle differences; and (3) Based on the above centerline detection roughly, the centerline points are searched in the original image in a local window along the direction perpendicular to the normal of the centerline, then these points are linked. A number of rock fracture images have been tested, and the testing results show that compared to other traditional algorithms, the proposed algorithm can extract rock fracture centerlines accurately.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.6
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• pp.825-831
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• 2016

In this paper, a transimpedance amplifier based on a new DC offset cancellation (DCOC) method is proposed for WCDMA/LTE applications. The proposed method applies a sample and hold mechanism to the conventional DCOC method with a DC feedback loop. It prevents the removal of information around the DC, so it avoids signal-to-noise ratio degradation. It also reduces area and power consumption. It was designed in a $0.13{\mu}m$ deep n-well CMOS technology and drew a maximum current of 1.58 mA from a 1.2 V supply voltage. It showed a transimpedance gain of $80dB{\Omega}$, an input-referred noise current lower than 0.9 pA/${\surd}$Hz, an out-of-band input-referred 3rd-order intercept point more than 9.5 dBm, and an output DC offset lower than 10 mV. Its area is $0.46mm{\times}0.48mm$.