• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.3
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• pp.84-96
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• 1997

In this paper an efficient morphologica algorithm for reducing gaussian and impulse noise in gray-scale image is presented. Based on the edge information the input image is partitioned into a flat region and an edge region, then different algorithms are selectively applied to each region. in case of impulse noise, MGR (morphologica grayscale reconstruction) algorithm with directional SE (structuring element) is applied to the flat region. For theedge region opening-closing (closing-opening) is used instead of dialation (erosion), so that the remaining noise around large objects can be removed. In case of gaussian noise, 5*5 OCCO(opening closing closing opening) and 3*3 DMF(directional morphological filter ) are used for the flat region and the edgeregion, respectively. In order to remove discontinuity at the edge boundary, the algorithm uses 3*3 OCCO around the edge region to reconstruct the final image. Experimetnal results have shown that the proposed algorithm achieves a high performance in terms of noise removal, detail preservation, and NMSE.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.955-956
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• 2014

Active noise control is noise reduction method by generate anti-phase control signal for destructive interference of through control speaker. purpose of this paper is create a virtual control source at a using the DBAP(Distance Based Amplitude Panning) algorithm which is one of the three-dimensional sound reproduction method, and verified through the experimentally for noise control method through the virtual control source. We compared active noise method by using one control speaker with active noise control method by using DBAP algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.166-170
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• 2008

In this study, it proved that transfer path analysis is a proper technique to estimate the interior noise from comparing measured interior noise in case of 3 point supported engine mount system. And the simulation of the vibration isolation for active engine mount using FXLMS algorithm is performed. Also, it verified that reduction of estimated interior noise from transfer path analysis and simulation of the vibration isolation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.165-168
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• 2000

Engine noise is one of the major causes of the interior noise, and so has been studied in various ways in recent days. Recently air induction noise has been extensively studied to reduce the engine noise. Conventional method to reduce the noise is adding several resonators to the induction system. However this causes a reduction of engine output power and an increase of fuel consumption. Thus in this study, the feasibility of applying the active noise control to the induction system is studied to the overcome the above disadvantage.

• The Korean Journal of Nuclear Medicine Technology
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• v.28 no.1
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• pp.35-40
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• 2024

Purpose: To improve the image quality in positron emission tomography (PET), the attenuation correction technique based on the computed tomography (CT) data is important process. However, the artifact is caused by metal material during PET/CT scan, and the image quality is degraded. Therefore, the purpose of this study was to evaluate image quality according to with and without iterative metal artifact reduction (iMAR) algorithm using customized 3D printing phantom. Materials and Methods: The Hoffman and Derenzo phantoms were designed. To protect the gamma ray transmission and express the metal portion, lead substance was located to the surface. The SiPM based PET/CT was used for acquisition of PET images according to application with and without iMAR algorithm. The quantitative methods were used by signal to noise ratio (SNR), coefficient of variation (COV), and contrast to noise ratio (CNR). Results and Discussion: The results shows that the image quality applying iMAR algorithm was higher 1.15, 1.19, and 1.11 times than image quality without iMAR algorithm for SNR, COV, and CNR. Conclusion: In conclusion, the iMAR algorithm was useful for improvement of image quality by reducing the metal artifact lesion.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1120-1125
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• 2010

In the speech system, for example hearing aid as well as speech communication, speech quality is degraded by environmental noise. In this study, to enhance the speech quality which is degraded by environmental speech, we proposed an algorithm to reduce the noise and reinforce the speech. The minima controlled recursive averaging (MCRA) algorithm is used to estimate the noise spectrum and spectral weighting factor is used to reduce the noise. And partial masking effect which is one of the human hearing properties is introduced to reinforce the speech. Then we compared the waveform, spectrogram, Perceptual Evaluation of Speech Quality (PESQ) and segmental Signal to Noise Ratio (segSNR) between original speech, noisy speech, noise reduced speech and enhanced speech by proposed method. As a result, enhanced speech by proposed method is reinforced in high frequency which is degraded by noise, and PESQ, segSNR is enhanced. It means that the speech quality is enhanced.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.568-574
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• 2002

The main issue of noise reduction of image is how to preserve edge and reduce noise. Usually, The Wiener falter is used for this purpose. But the conventional Wiener filter cannot remove noise well in both edge and smooth region due to the single size estimation window. In addition, it ignores the correlation between pixels. In this paper, we propose a new noise reduction algorithm, in which adaptive estimation window is used according to property of smooth region and edge region. In order to make edge more clear, directional Gaussian mask and directional estimation window combines to the Wiener filter according to direction of edge. From the simulation results, it can be seen that the proposed algorithm showed improves performance in both PSNR arid subjective evaluation

• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.568-579
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• 2015

Recently, mobile devices with touch display panel are widely used. Accuracy and reaction speed of touch signal are very important in touch devices. Therefore, we need to develop an effective algorithm to reduce touch noise quickly and accurately. This paper proposes a touch noise reduction algorithm using Kalman filtering in consideration of signal motion. First, a specific pre-emphasis processing is applied to an input signal so as to maximize the effect of Kalman filtering. In other words, a pure signal in the touch signal increases but noise in the touch signal decreases. Next, motion of the signal is detected. Motion estimation is performed only if motion is detected. If we detect motion by using the only neighborhood of the signal, we can reduce about 75% of the computation in comparison with examining the entire area. Finally, Kalman filtering using the previous state of current signal is performed. Experimental results show that the proposed algorithm suppresses touch noise sufficiently without degradation of the pure signal

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.133-139
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• 2011

In this paper, we propose a hybrid filter for noise reduction. The proposed method adjusts rational filtering direction according to an edge in the image using median filtered data. Rational filter modulates the coefficients of a linear lowpass filter to limit its action in presence of image details. By the ratio of polynomials in the input variables, rational filter reduces noise adaptively. Median filter is widely used to reduce impulse noise, but removes some details for highly corrupted images. Also, desirable details are removed when the window size is large. Our proposed algorithm combines rational filter and median filter. Thus, proposed method not only preserves edge, but also reduces noise in uniform region. Experimental results show that our proposed method has better quality than those by existing median and rational filtering methods.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.367-368
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• 2007

In this paper, we propose a new de-noising algorithm for 2 dimensional image using discrete wavelet transform. The proposed algorithm consists of edge detection in spatial domain, zero-tree estimation, subband estimation, and shrinkage algorithm. The results from it shows that the denoised image which Is damaged by 20% gaussian noise has 28dB quality for the original one.