• The Journal of the Korea Contents Association
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• v.18 no.3
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• pp.299-308
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• 2018

This study focused on the fact that medical images that are issued at different hospitals may affect image quality on PACS when different software is used. A university hospital image was copied to the DICOM file and registered on the PACS of the university hospital B. The capacity and image quality of the software used in the university hospital were evaluated by SNR, CNR and histogram. As the compression ratio increased, SNR and CNR tended to decrease. Note that Lossless Compression decreased the data size by half compared to No Compression, but SNR and CNR did not change. As a result of the histogram analysis, the information loss due to the underflow phenomenon was conspicuous. When moving to another hospital, No compression or lossless compression method should be used. In conclusion, it is useful to use the lossless compression method, considering waiting time and economic efficiency in uploading.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.101-107
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• 2011

The background noises and distortions by channel are major factors that disturb the practical use of speech recognition. Usually, noise reduce the performance of speech recognition system DSR(Distributed Speech Recognition) based speech recognition also bas difficulty of improving performance for this reason. Therefore, to improve DSR-based speech recognition under noisy environment, this paper proposes a method which detects accurate speech region to extract accurate features. The proposed method distinguish speech and noise by using entropy and detection of spectral energy of speech. The speech detection by the spectral energy of speech shows good performance under relatively high SNR(SNR 15dB). But when the noise environment varies, the threshold between speech and noise also varies, and speech detection performance reduces under low SNR(SNR 0dB) environment. The proposed method uses the spectral entropy and harmonics of speech for better speech detection. Also, the performance of AFE is increased by precise speech detections. According to the result of experiment, the proposed method shows better recognition performance under noise environment.

• The Journal of the Acoustical Society of Korea
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• v.29 no.4
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• pp.278-285
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• 2010

The difference between training and test environments is one of the major performance degradation factors in noisy speech recognition and many silence feature normalization methods were proposed to solve this inconsistency. Conventional silence feature normalization method represents higher classification performance in higher SNR, but it has a problem of performance degradation in low SNR due to the low accuracy of speech/silence classification. On the other hand, cepstral distance represents well the characteristic distribution of speech/silence (or noise) in low SNR. In this paper, we propose a Cepstral distance and Log-energy based Silence Feature Normalization (CLSFN) method which uses both log-energy and cepstral euclidean distance to classify speech/silence for better performance. Because the proposed method reflects both the merit of log energy being less affected with noise in high SNR and the merit of cepstral distance having high discrimination accuracy for speech/silence classification in low SNR, the classification accuracy will be considered to be improved. The experimental results showed that our proposed CLSFN presented the improved recognition performances comparing with the conventional SFN-I/II and CSFN methods in all kinds of noisy environments.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.2
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• pp.126-136
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• 1997

When we apply the spectrally efficient quadrature amplitude modulation(QAM) to mobile communications, it is necessary to estimate and compensate the channel charac- teristics. In this paper, a new type fading estimation method for PSAM using sinc function is presented. Gaussian interpolation method has a drawback that the performance degrades rapidly if pilot symbol period increases even though pilot sysbol period is less than Nyquist sampling rate. The Wiener filter method does not degrade until pilot symbol period is equal to the Nyquist sampling rate. It is difficult for Wiener filter method to be applied to real system because autocorrelation function of channel gain, Doppler frequency and SNR(signal to noise ratio) must be known to optimize the filter coefficients. But proposed method has a similar performance to the Wiener filter method, and does not need to know the autocorrelation function of channel gain, the doppler frequency and SNR. Therefore the proposed method cna be applied to real system easily.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.11
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• pp.933-940
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• 2021

The space-borne SAR(Synthetic Aperture Radar) system radiates the microwave signal and receives the backscattered signal. The received signal is converted to digital at the Digital Receiver, which is implemented at the end of the SAR sensor receiving chain. The converted signal is formated after signal processing such as filtering and data compression. Two quantization are conducted in the Digital Receiver. One quantization is an analog to digital conversion at ADC(Analog-Digital Converter). Another quantization is the BAQ(Block Adaptive Quantization) for data compression. The quantization process is a conversion from a continuous or higher bit precision to a discrete or lower bit precision. As a result, a quantization noise is inevitably occurred. In this paper, the impact of two quantization processes are analyzed in a view of SNR degradation.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.417-422
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• 2023

In this study, normal saline was diluted with the contrast medium at a certain ratio for the purpose of reducing the image quality poor and side effects caused by the contrast medium during CT examination. At this time, by finding the energy level of DECT that can compensate for the decrease in contrast of the image according to the degree of dilution, the usefulness of applying DECT for compensating the difference in image contrast was investigated through comparative analysis by applying SNR, CNR, and SSIM. As a result, when a dilution ratio of 4 (contrast medium): 6 (normal saline) and the energy level of DECT of 65 keV were applied, the contrast difference was the most similar to that when using the undiluted contrast medium. At this time, SNR was 813.71 ± 37.6, CNR was the highest at 921.87 ± 17.1, and SSIM index was measured at 0.851, which is the most similar to 1. The results of this study are meaningful in providing basic information for finding the appropriate dilution rate and energy level for each examination site through future clinical studies. It is believed that it can be reduced.

• The Journal of the Acoustical Society of Korea
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• v.29 no.7
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• pp.468-474
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• 2010

The major factor that disturbs practical use of speech recognition is distortion by the ambient and channel noises. Generally, the ambient noise drops the performance and restricts places to use. DSR (Distributed Speech Recognition) based speech recognition also has this problem. Various noise cancelling algorithms are applied to solve this problem, but loss of spectrum and remaining noise by incorrect noise estimation at low SNR environments cause drop of recognition rate. This paper proposes methods for speech enhancement. This method uses MMSE-STSA for noise cancelling and ideal binary mask to compensate damaged spectrum. According to experiments at noisy environment (SNR 15 dB ~ 0 dB), the proposed methods showed better spectral results and recognition performance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.1-2
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• 2023

본 연구는 환경 요인이 통제되어 있는 실험실 데이터에 산업 현장에서 발생하는 유사 잡음을 노이즈로 추가하였을 때, SNR비에 따른 노이즈별 STFT Log Spectrogram, Mel-Spectrogram, CWT Spectrogram 총 3가지의 이미지를 생성하고, 각 이미지를 입력으로 한 CNN 결함 분류 모델의 성능 결과를 확인하였다. 원본 데이터의 영향력이 큰 0db 이상의 SNR비로 합성할 경우 원본 데이터와 분류 결과상 큰 차이가 존재하지 않았으며, 노이즈 데이터의 영향이 큰 0db 이하의 SNR비로 합성할 경우, -20db의 STFT 이미지 기준 약 26%의 성능 저하가 발생하였다. 또한, Wiener Filtering을 통한 디노이징 처리 이후, 노이즈를 효과적으로 제거하여 분류 성능의 결과가 높아지는 점을 확인하였다.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.5
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• pp.153-160
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• 2004

In this paper, we propose an efficient bit loading algorithm for IEEE 802.11a wireless LAN systems. While a conventional bit loading algorithm uses the SNR value of each subcarrier, it is very difficult to estimate the exact SNR value in wireless LAN systems due to randomness of AWGN. Therefore, in order to solve this problem our proposed algorithm uses the channel frequency response instead of the SNR of each subcarrier. Through simulation results, we can obtain the performance gain of 3.5∼8㏈ at PER of 10-2 with the proposed bit loading algorithm while the conventional one obtains the performance gain of 0.5∼5㏈ at the same conditions. Also, the increased data rate can be confirmed 63Mbps. After the logic synthesis using 0.3${\mu}{\textrm}{m}$ CMOS technology, the logic gate count for the processor with proposed algorithm can be reduced by 34% in comparison with the conventional one.

• 전자공학회논문지 IE
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• v.49 no.2
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• pp.9-17
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• 2012

One of the problems on the application of the speech recognition system in the real world is the degradation of the performance by acoustical distortions. The most important source of acoustical distortion is the additive noise. This paper describes a spectral compensation technique based on a spectral peak enhancement scheme followed by an efficient noise subtraction scheme for noise robust speech recognition. The proposed methods emphasize the formant structure and compensate the spectral tilt of the speech spectrum while maintaining broad-bandwidth spectral components. The recognition experiments was conducted using noisy speech corrupted by white Gaussian noise, car noise, babble noise or subway noise. The new technique reduced the average error rate slightly under high SNR(Signal to Noise Ratio) environment, and significantly reduced the average error rate by 1/2 under low SNR(10 dB) environment when compared with the case of without spectral compensations.