• Proceedings of the IEEK Conference
• /
• summer
• /
• pp.199-203
• /
• 2004

In this paper, we only describe the digital block of two-channel 18-bit analog-to-digital (A/D) converter employing sigma-delta method and xl28 decimation. The device contains two fourth comb filters with 1-bit input from sigma­delta modulator. each followed by a digital half band FIR(Finite Impulse Response) filters. The external analog sigma-delta modulators are sampled at 6.144MHz and the digital words are output at 48kHz. The fourth-order comb filter has designed 3 types of ways for optimal power consumption and signal-to-noise ratio. The following 3 digital filters are designed with 12tap, 22tap and 116tap to meet the specification. These filters eliminate images of the base band audio signal that exist at multiples of the input sample rate. We also designed these filters with 8bit and 16bit filter coefficient to analysis signal-to-noise ratio and hardware complexity. It also included digital output interface block for I2S serial data protocol, test circuit and internal input vector generator. It is fabricated with 0.35um HYNIX standard CMOS cell library with 3.3V supply voltage and the chip size is 2000um by 2000um. The function and the performance have been verified using Verilog XL logic simulator and Matlab tool.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.38 no.2
• /
• pp.1-5
• /
• 2001

We propose an optical performance monitoring method for WDM optical transmission systems. By assigning a pair of AWG ports to each optical signal channel. the optical power, optical signal-to-noise ratio (OSNIO, and wavelength of all the signal channels are observed simultaneously. The output power ratio of the AWG port pair depended on the wavelength variation of the channel with sensitivity of 1dB/0.026nm. The OSNH results were deviated no more than 0.7dB from the results measured by optical signal analyzer (OSA).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.05a
• /
• pp.932-935
• /
• 2015

Recently, the image system is utilized in several fields due to the development of multimedia technology. However, the noise occurs according to various causes in the process of image data processing. The noises added to the image include several types according to the cause and shape, and the salt and pepper noise is one of the typical noise types. Thus, this paper proposed the median filter algorithm using the estimated mask in order to remove the salt and pepper noise effectively and also compared this algorithm with the current methods using PSNR(peak signal to noise ratio) as a criterion of judgment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.05a
• /
• pp.281-284
• /
• 2015

Digital image processing is utilized in various application fields by rapid development of memory cell. However, the noise occurs with various causes in the process of data processing process and various methods have been studied in order to remove such noises. In general, the image is damaged by the mixed noise which has different characteristics each other. This paper proposed a filter algorithm which processes the data according to shape of noise in order to mitigate the impact of the mixed noise added to the image. In addition, this paper compared this filter algorithm with the current methods and used PSNR(peak signal to noise ratio) as a criterion of judgment.

• Investigative Magnetic Resonance Imaging
• /
• v.8 no.1
• /
• pp.42-49
• /
• 2004

Purpose : The quantization noise in magnetic resonance imaging (MRI) systems is analyzed. The signal-to-quantization noise ratio (SQNR) in the reconstructed image is derived from the level of quantization in the signal in spatial frequency domain. Based on the derived formula, the SQNRs in various main magnetic fields with different receiver systems are evaluated. From the evaluation, the quantization noise could be a major noise source determining overall system signal-to-noise ratio (SNR) in high field MRI system. A few methods to reduce the quantization noise are suggested. Materials and methods : In Fourier imaging methods, spin density distribution is encoded by phase and frequency encoding gradients in such a way that it becomes a distribution in the spatial frequency domain. Thus the quantization noise in the spatial frequency domain is expressed in terms of the SQNR in the reconstructed image. The validity of the derived formula is confirmed by experiments and computer simulation. Results : Using the derived formula, the SQNRs in various main magnetic fields with various receiver systems are evaluated. Since the quantization noise is proportional to the signal amplitude, yet it cannot be reduced by simple signal averaging, it could be a serious problem in high field imaging. In many receiver systems employing analog-to-digital converters (ADC) of 16 bits/sample, the quantization noise could be a major noise source limiting overall system SNR, especially in a high field imaging. Conclusion : The field strength of MRI system keeps going higher for functional imaging and spectroscopy. In high field MRI system, signal amplitude becomes larger with more susceptibility effect and wider spectral separation. Since the quantization noise is proportional to the signal amplitude, if the conversion bits of the ADCs in the receiver system are not large enough, the increase of signal amplitude may not be fully utilized for the SNR enhancement due to the increase of the quantization noise. Evaluation of the SQNR for various systems using the formula shows that the quantization noise could be a major noise source limiting overall system SNR, especially in three dimensional imaging in a high field imaging. Oversampling and off-center sampling would be an alternative solution to reduce the quantization noise without replacement of the receiver system.

• Journal of Information Processing Systems
• /
• v.14 no.4
• /
• pp.941-947
• /
• 2018

Since the amplitudes of spin echo train in nuclear magnetic resonance logging (NMRL) are small and the signal to noise ratio (SNR) is also very low, this paper puts forward an improved de-noising algorithm based on wavelet transformation. The steps of this improved algorithm are designed and realized based on the characteristics of spin echo train in NMRL. To test this improved de-noising algorithm, a 32 points forward model of big porosity is build, the signal of spin echo sequence with adjustable SNR are generated by this forward model in an experiment, then the median filtering, wavelet hard threshold de-noising, wavelet soft threshold de-noising and the improved de-noising algorithm are compared to de-noising these signals, the filtering effects of these four algorithms are analyzed while the SNR and the root mean square error (RMSE) are also calculated out. The results of this experiment show that the improved de-noising algorithm can improve SNR from 10 to 27.57, which is very useful to enhance signal and de-nosing noise for spin echo train in NMRL.

• Proceedings of the KOSOMBE Conference
• /
• v.1995 no.11
• /
• pp.265-268
• /
• 1995

Signal averaging technique to improve signal-to-noise ratio has widely been used in various fields, especially in electrophysiology. Estimation of the EP(evoked potential) signal using the conventional averaging method fails to correctly reconstruct the original signal under EEG(electroencephalogram) noise especial]y when the latency times of the evoked potential are not identical. Therefore, a technique based on the bispectrum averaging was proposed for recovering signal waveform from a set o noisy signals with variable signal dalay. In this paper an improved bispectrum estimation technique of the RP signal is proposed using a confidence thresholding of the EP signal in frequency domain in which energy distribution of the EP signal is usually not uniform. The suggested technique is coupled with the conventional bispectrum estimation technique such as least square method and recursive method. Some results with simulated data and real EP signal are shown.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.4
• /
• pp.728-732
• /
• 2010

GIS(Gas insulated switching gear) is power equipment with excellent dielectric strength and is economy merit in high confidence and stability. Recently, because equipment of GIS was occurring problem of confidence used for a long time, partial discharge on-line diagnosis systems have been importantly recognized. Partial discharge (PD) detection is an effective means for monitoring and evaluation of dielectric condition of gas insulated system (GIS). The ultra-high-frequency (UHF) PD detection technique can detect and locate the PD sources inside GIS by detecting electromagnetic wave emitted from PD source. Therefore, real-time diagnostic system using UHF detection method has been developed for this application is being expanded gradually. However, the signal of partial discharge occurring in SF6 gas is very weak and susceptible to external noises which mainly consist of PD in air. Thus, it is important to distinguish the PD in SF6 gas more sensitively from the external noises. Unfortunately, these external noise signals and the partial discharge signals have very similar characteristics. Therefore, to solve this problem, we need the signal processing method for distinguish partial discharge signals with external noise signals for improvement of SNR(signal to noise ratio) and sensitivity. In this paper, we proposed internal signal processing method for removing external noise signals with built-in pre.amplifier and frequency conversion circuit.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.5
• /
• pp.2197-2204
• /
• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

• Journal of information and communication convergence engineering
• /
• v.6 no.1
• /
• pp.80-85
• /
• 2008

Images are often corrupted by noises during signal acquisition and transmission. Among those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. For different types of noise have different characters, how to remove them separately from degraded image is one of the most fundamental problems. Thus, a modified image restoration algorithm is proposed in this paper, which can not only remove impulse noise of random values, but also remove the AWGN selectively. The noise detection step is by calculating the intensity difference and the spatial distance between pixels in a mask. To divide two different noises, the method is based on three weighted parameters. And the weighted parameters in the filtering mask depend on spatial distances, positions of impulse noise and standard deviation of AWGN. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, and simulation results demonstrate that the proposed method performs better than conventional median-type filters, in preserving edge details.