• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.63-69
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• 2017

In order to observe the noise property of the flat-panel digital radiography detector, measuring the normalized noise power spectrum (NNPS) from acquired x-ray images is conducted. However, the conventional NNPS measurement has an unstable property depending on the acquired image. Averaging the sample periodograms of the input image is usually performed to estimate the NNPS values and increasing the number of samples can provide a reliable NNPS measurement. In this paper, for a finite number of images, two measurement methods, which are based on averaging spectra, such as the image periodogram, are proposed and their performances are analyzed. Using x-ray images acquired from two types of radiography detectors, the two spectrum averaging methods are compared and it is shown that averaging spectra based on the maximal number of combinations of the image pairs provides the best performance in measuring NNPS.

• The Journal of the Acoustical Society of Korea
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• v.27 no.1E
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• pp.1-10
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• 2008

A noise suppression algorithm is proposed for nonstationary noisy environments. The proposed algorithm is different from the conventional approaches such as the spectral subtraction algorithm and the minimum statistics noise estimation algorithm in that it classifies speech and noise signals in time-frequency bins. It calculates the ratio of the variance of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. If the ratio is greater than an adaptive threshold, speech is considered to be present. Our adaptive algorithm tracks the threshold and controls the trade-off between residual noise and distortion. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of simplicity and light computational load for estimating the noise. This algorithm reduces the residual noise significantly, and is superior to the conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.13 no.6
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• pp.66-74
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• 1994

Simulation of sonar reverberation time series is very useful because most acoustic models are power level models and have a difficulty when performance of hardware system is evaluated under the reverberant condition. Thus, in this paper, the simulation of reverberation time series is attempted, First, normalized spectrum, whose bandwidth is varying in the frequency domain and which has zero-mean Gaussian distribution, is calculated at pre-selected receiving time. Second, reverberation levels given by underwater acoustic model are combined with normalized spectrum in the frequency domain. Finally, nonstationary sonar reverberation time series are simulated by IFT(Inverse Fourier Transform).

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.120-127
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• 2016

In order to acquire digital x-ray images, developing radiography detectors have been recently conducted based on the DR (digital radiography) technology. The noise property of the radiography detector can be observed from measuring the NNPS (normalized noise power spectrum) using uniform exposure images. Here, the image difference of two images is used to remove the fixed pattern noise in measuring the detector NNPS. In this paper, two average images are first calculated using several images and then their difference is used to calculate an NNPS value. Here, the obtained NNPS value is usually lower than the true detector NNPS due to the average. Hence, a compensation constant, which is a function of the number of used images, is also proposed to compensate the NNPS value to obtain the true detector NNPS. Furthermore, another measurement method, in which the ratio of the average images is used, is proposed. Through NNPS measuring experiments using real x-ray images, it is observed that the proposed method can provide further accurate NNPS measurements.

• Journal of Acupuncture Research
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• v.28 no.2
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• pp.27-41
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• 2011

Objectives : The aim of this study was to examine the effect of manual acupuncture at the bilateral $LI_4$, $ST_{36}$ and $LR_3$ on normal human every 3 minute time interval by using power spectrum analysis. Methods : 25 healthy volunteers participated in this study. 32 channel EEG(Electroencephalogram) measurements were carried out before, during and after acupuncture treatments. In this study, power spectrum was used as a measure of complexity. Statistical analysis was performed using repeated measure ANOVA and Bonferroni method. Results : 1. In acupuncture group, Mean HRT, PSI, Normalized HF decreased significantly. SDNN, Ln(TP), Ln(LF), Ln(VLF), Normalized LF and LF/HF ratio increased significantly. RMSSD, Ln(HF) were not affected. 2. In sham acupuncture group, all indicators were not affected. 3. In control group, mean HRT, Ln(TP) decreased significantly. SDNN, RMSSD, PSI, Ln(LF), Ln(HF), Ln(VLF), normalized LF, normalized HF and LF/HF ratio were not affected. Conclusions : This results suggest that manipulation needling of 6 acupoints induced increase of delta, theta, beta waves. Both manipulation and simple needling induced decrease of alpha wave during 12~15 time intervals.

• 전기의세계
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• v.34 no.2
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• pp.94-98
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• 1985

Autocorrelation에 관계되는 Fourier변환의 기본적인 성질을 이용하여 speckle잡음제거가 power spectrum estimation 문제와 같이 해석될 수 있다는 것을 보였고 spectral estimation 방법으로서 최대 entrppy방법을 사용하여 딴 방법들과 비교하여 볼때 좋은 결과를 얻었다. 앞으로 2차원 test object까지의 확장, 이 알고리즘의 각 파라메타들에 대한 sensitivity, optimal한 Hanning window크기 판단 기준으로서 normalized mean squared error(NMSE)를 사용하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.87-94
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• 2009

Noise estimation and suppression are a crucial factor of many speech communication and recognition systems. In this paper, proposed algorithm is based on the ratio of variance normalized of noisy power spectrum in time-frequency domain. Our proposed algorithm tracks the threshold and controls the trade-off between residual noise and distortion. This algorithm is evaluated by the ITU-T P.835 signal distortion (SIG) and segment signal to noise ratio (SNR), and is superior to the conventional methods.

• Journal of Acupuncture Research
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• v.22 no.6
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• pp.173-180
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• 2005

Objectives : The purpose of this study was to assess the effect auricular acupuncture for acute mental stress using power spectrum analysis of the heart rate variability(HRV). Methods : 10 healthy volunteers participated in this study. After 5 minute rest, the first mental stress was provided for 5 minute. And then subjects rested for 15 minute. The second mental stress was provided for 5 minute. The acupoint, Shin-Mun point of the ear was stimulated for 15 minute. HRV was recorded before and after the first and second mental stress, and after auricular acupuncture stimulation. Results : After mental stress, normalized LF and LF/HF ratio is significantly increased. Before and after simple rest, normalized LF and normalized HF is significantly changed, but LF and LF/HF ratio is not significantly changed. On the other hand, before and after auricular acupuncture treatment, normalized LF, normalized HF is significantly changed, and also LF and LF/HF ratio is significantly decreased. Conclusion : The result suggest that auricular acupuncture can decrease more significantly in cardiac sympathetic activity due to mental stress than simple rest.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.818-827
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• 2008

In this paper, we propose a new noise estimation and reduction algorithm for stationary and nonstationary noisy environments. This approach uses an algorithm that classifies the speech and noise signal contributions in time-frequency bins. It relies on the ratio of the normalized standard deviation of the noisy power spectrum in time-frequency bins to its average. If the ratio is greater than an adaptive estimator, speech is considered to be present. The propose method uses an auto control parameter for an adaptive estimator to work well in highly nonstationary noisy environments. The auto control parameter is controlled by a linear function using a posteriori signal to noise ratio(SNR) according to the increase or the decrease of the noise level. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of much more simplicity and light computational load for estimating the stationary and nonstationary noise environments. The proposed algorithm is superior to conventional methods. To evaluate the algorithm's performance, we test it using the NOIZEUS database, and use the segment signal-to-noise ratio(SNR) and ITU-T P.835 as evaluation criteria.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.37-41
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• 1995

In this paper, we proposed the 2-stage ultrasound liver image classifier which uses the fractal dimensions obtained from the original image and its 1/2 subsampled image, and the Normalized Fourier Power Spectrum. The fractal dimension based on Fractional Brownian Motion (FBM) is calculated from the variance of the same scale pixels instead of the mean of them. Since the actual ultrasound. liver images does not fully match the FBM, to get the fractal dimension, we use the scale vectors which satisfy the FBM model. In 2-stage classifier, we first classified normal and diffuse liver and then classified the fat liver and cirrhosis from the diffuse liver. For the test liver images. 70% of normal liver and 80% of fat liver and 90% of cirrhosis is classified classified with our 2-stage classifier.