• The Journal of the Acoustical Society of Korea
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• 제27권1E호
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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.

• 전자공학회논문지
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• 제54권3호
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• pp.63-69
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• 2017

NNPS(normalized noise power spectrum)는 획득한 x선 영상에서 평판형 방사선 디텍터의 잡음 특성을 spectrum을 관찰하기 위해 측정한다. 그러나 NNPS 측정은 획득한 영상에 따라 일관적이지 못한 성질을 가지고 있어서 안정된 측정이 필요하다. 디텍터의 NNPS 측정은 표본 periodogram을 구하여 평균을 내는 방법을 사용하는데, 일반적으로 표본의 개수를 충분히 늘리면 정확하면서 안정된 값을 구할 수 있다. 본 논문에서는 periodogram과 같은 표본 spectrum의 평균으로 유한한 개수의 영상이 주어졌을 때 일관적이고 효율적인 NNPS 값을 제공 할 수 있는 두 가지 방법을 제안하고 그 성능을 비교하고 분석했다. 실제 두 종류의 방사선 디텍터로부터 획득한 x선 영상을 사용하여 제안한 방법을 실험하였으며, 주어진 영상을 사용하여 표본 spectrum의 최대 가지 수를 갖는 조합으로 NNPS를 구하고 평균을 내는 방법이 기존 방법에 비하여 안정된 NNPS 측정이 가능함을 보였다.

• 전자공학회논문지
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• 제53권12호
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• pp.120-127
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• 2016

디지털 x선 영상을 획득하기 위하여 최근에는 DR(digital radiography) 기술에 근거한 방사선 디텍터의 개발이 활발하게 진행되고 있다. 이러한 방사성 디텍터의 잡음 특성은, 균일한 노출에서 획득한 영상을 사용하여 NNPS(normalized noise power spectrum)를 측정하여 관찰한다. 이때 고정형태잡음(fixed pattern noise)을 제거하기위하여 두 장의 영상 차를 사용한다. 본 논문에서는 보다 정확한 NNPS를 측정하기 위하여, 먼저 여러 장의 영상을 획득하여 두 장의 평균영상을 구하고 그의 차를 사용하여 NNPS를 구하는 방법을 제안하였다. 이때 여러 장의 영상들의 평균으로 인하여 NNPS 값이 실제 값보다 작아지는데, 이러한 NNPS의 보정을 위하여, 평균할 때 사용한 영상 개수의 함수인 보정 상수도 함께 제안하였다. 또한 평균영상의 비를 사용하여 NNPS를 구하는 방법도 제안하였다. 실제 방사선 디텍터에서 획득한 영상을 사용하여 NNPS를 측정하는 실험을 통하여, 제안한 방법으로 NNPS 보다 정확하게 구할 수 있음을 관찰하였다.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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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.

• 대한전자공학회논문지SP
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• 제46권1호
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• pp.87-94
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• 2009

잡음예측 및 저감방법은 음성통신과 인식분야의 중요한 핵심기술이다. 본 논문에서는 다양한 잡음환경에 적용할 수 있는 새로운 잡음예측 및 저감 방법을 제안한다. 제안된 알고리즘은 시간 및 주파수영역의 noisy power spectrum 의 분산과 그 값의 정규화 ratio를 기반으로 한다. 제안한 방법은 다양한 잡음환경에서 잘 동작 할 수 있도록 적응추적 임계값을 사용하며, 이 임계값은 음성왜곡과 잔여잡음 사이의 trade-off를 제어한다. 새로운 알고리즘의 성능은 다양한 잡음환경에서 ITU-T P.835(SIG) and segment (SNR) 의해 평가하여 기존의 방법에 비해 향상된 결과를 나타냈다.

• The Journal of the Acoustical Society of Korea
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• 제26권3E호
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• pp.87-96
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• 2007

In this paper we propose a new noise reduction algorithm for stationary and nonstationary noisy environments. Our algorithm classifies the speech and noise signal contributions in time-frequency bins, and is not based on a spectral algorithm or a minimum statistics approach. It relies on calculating the ratio of the standard deviation of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. We show that good quality can be achieved for enhancement speech signal by choosing appropriate values for ${\delta}_t\;and\;{\delta}_f$. The proposed method greatly reduces the noise while providing enhanced speech with lower residual noise and somewhat higher mean opinion score (MOS), background intrusiveness (BAK) and signal distortion (SIG) scores than conventional methods.

• Nuclear Engineering and Technology
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• 제52권11호
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• pp.2594-2600
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• 2020

A gamma camera system using radionuclide has a functional imaging technique and is frequently used in the field of nuclear medicine. In the gamma camera, it is extremely important to improve the image quality to ensure accurate detection of diseases. In this study, we designed a blind-deconvolution framework after a noise-reduction algorithm based on a non-local mean, which has been shown to outperform conventional methodologies with regard to the gamma camera system. For this purpose, we performed a simulation using the Monte Carlo method and conducted an experiment. The image performance was evaluated by visual assessment and according to the intensity profile, and a quantitative evaluation using a normalized noise-power spectrum was performed on the acquired image and the blind-deconvolution image after noise reduction. The result indicates an improvement in image performance for gamma camera images when our proposed algorithm is used.

• Nuclear Engineering and Technology
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• 제51권3호
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• pp.719-722
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• 2019

Gamma-ray images generally suffer from a lot of noise because of low photon detection in the gamma camera system. The purpose of this study is to improve the image quality in gamma-ray images using a gamma camera system with a fast nonlocal means (FNLM) noise reduction algorithm with an acceleration function. The designed FNLM algorithm is based on local region considerations, including the Euclidean distance in the gamma-ray image and use of the encoded information. To evaluate the noise characteristics, the normalized noise power spectrum (NNPS), contrast-to-noise ratio (CNR), and coefficient of variation (COV) were used. According to the NNPS result, the lowest values can be obtained using the FNLM noise reduction algorithm. In addition, when the conventional methods and the FNLM noise reduction algorithm were compared, the average CNR and COV using the proposed algorithm were approximately 2.23 and 7.95 times better than those of the noisy image, respectively. In particular, the image-processing time of the FNLM noise reduction algorithm can achieve the fastest time compared with conventional noise reduction methods. The results of the image qualities related to noise characteristics demonstrated the superiority of the proposed FNLM noise reduction algorithm in a gamma camera system.

• Journal of Magnetics
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• 제21권4호
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• pp.593-598
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• 2016

In order to reduce the amount of noise component in X-ray imaging system, various reduction techniques were frequently used in the field of diagnostic imaging. Although the previous techniques -such as median, Wiener filters and Anscombe noise reduction technique - were able to reduce the noise, the edge information was still damaged. In order to cope with this problem, total variation (TV) noise reduction technique has been developed and researched. The purpose of this study was to evaluate and compare the image quality using normalized noise power spectrum (NNPS) and contrast-to-noise ratio (CNR) through simulations and experiments with respect to the above-mentioned noise reduction techniques. As a result, not only lowest NNPS value but also highest CNR values were acquired using a TV noise reduction technique. In conclusion, the results demonstrated that TV noise reduction technique is proved as the most practical method to ensure accurate denoising in X-ray imaging system.

• Nuclear Engineering and Technology
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• 제51권2호
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• pp.439-443
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• 2019

To improve the noise characteristics, software-based noise reduction algorithms are widely used in cadmium zinc telluride (CZT) pixelated semiconductor gamma camera system. The purpose of this study was to develop an improved median filtering algorithm using a thresholding method for noise reduction in a CZT pixelated semiconductor gamma camera system. The gamma camera system simulated is a CZT pixelated semiconductor detector with a pixel-matched parallel-hole collimator and the spatial resolution phatnom was designed with the Geant4 Application for Tomography Emission (GATE). In addition, a noise reduction algorithm with a median filter using an improved thresholding method is developed and we applied our proposed algorithm to an acquired spatial resolution phantom image. According to the results, the proposed median filter improved the noise characteristics compared to a conventional median filter. In particular, the average for normalized noise power spectrum, contrast to noise ratio, and coefficient of variation results using the proposed median filter were 10, 1.11, and 1.19 times better than results using conventional median filter, respectively. In conclusion, our results show that the proposed median filter using improved the thresholding method results in high imaging performance when applied in a CZT semiconductor gamma camera system.