• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.343-345
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• 2017

In digital era image processing has been utilized in a variety of media such as TV, camera and smart phone. However, in the process of analyzing, recognizing, and processing image data, deterioration occurs due to various causes and Salt & Pepper noise occurs. Typical methods for removing such noise include SMF, CWMF, and SWMF. However, existing methods have a somewhat poor noise canceling characteristic in Salt & Pepper noise environment. Therefore, in this paper, we propose an algorithm to remove Salt & Pepper noise effectively by using bilinear interpolation method and median filter according to noise density of local mask. And using the PSNR(Peak Signal to Noise Ratio) it compared to the existing methods and their performance in order to determine the performance of the proposed method.

• Geophysics and Geophysical Exploration
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• v.25 no.2
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• pp.71-84
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• 2022

When acquiring seismic data, various types of simultaneously recorded seismic noise hinder accurate interpretation. Therefore, it is essential to attenuate this noise during the processing of seismic data and research on seismic noise attenuation. For this purpose, machine learning is extensively used. This study attempts to attenuate noise in prestack seismic data using unsupervised machine learning. Three unsupervised machine learning models, N2NUNET, PATCHUNET, and DDUL, are trained and applied to synthetic and field prestack seismic data to attenuate the noise and leave clean seismic data. The results are qualitatively and quantitatively analyzed and demonstrated that all three unsupervised learning models succeeded in removing seismic noise from both synthetic and field data. Of the three, the N2NUNET model performed the worst, and the PATCHUNET and DDUL models produced almost identical results, although the DDUL model performed slightly better.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.239-245
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• 2016

Deramping technique has been widely used to acquire high resolution SAR(Synthetic Aperture Radar) images for the advantage of the data size and the processing time. However, unwanted spurious signals caused by SAR hardware can be leaked in the process of converting into a digital signal through the ADC(Analog-Digital Converter) and added in a echo signal. These tones make image quality degrade significantly. In order to solve this problem, the unwanted tones need to be detected by analysing the characteristic of the noise tone and then effectively removed from raw data. In this paper, we propose a method for efficiently removing noise tone on the raw data based on the characteristic of spurious signals.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.4
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• pp.328-335
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• 2017

In this paper, we propose an efficient method to remove noise component contained in high resolution range profile(HRRP) to improve target identification performance. The proposed method can effectively eliminate the noise component using both the statistical characteristics of the noise component and EMD algorithm. Experimental results show that the proposed method can substantially improve the identification capability, removing the noise component effectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.883-885
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• 2013

Image restoration refers to removing different kinds of noise added to image, and to reducing effect of noise upon image. For image restoration, some methods such as mean filter, median filter and weighted filter were proposed, but the existing methods have poor denoising and edge-reserved performance. Therefore, in this paper modified median filter algorithm was proposed that enlarges mask size according to median value of mask in order to remove noise efficiently. And, it was compared by simulation to the existing methods, and MSE(mean squared error) was used on a criterion of evaluation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.268-270
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• 2013

According to the development and supply of Wibro technology digital technology is applied in several fields. Digital images are damaged by various noises in the process of transfer and storage; the image restoration is to reduce the influence of the noises on images by removing the noises. To make good image restoration several methods have been proposed but the noise removal property is not satisfactory. Therefore, to effectively remove noises noise decision is made and if it is decided as a noise, the size of mask is enlarged; this is adaptive median filter algorithm that is proposed in this paper. And through simulation the superiority of this algorithm to existing methods has been verified.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2300-2307
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• 2008

This study receives the noise transmitted in a constant audio frequency range through a microphone array in which the noise(like grease in a pan) occurs on the power supply line due to the troublesome partial discharge(arc). Then by going through a series of signal processing of removing noise, this study measures the distance and direction up to the noise caused by the troublesome partial discharge(arc) and monitors the result by displaying in the analog and digital method. After these, it determines the state of each size and judges the distance and direction of problematic part. When the signal sound transmitted by the signal source of bad insulator is received on each microphone, the signal comes only in the frequency range of 20 kHz by passing through the circuit of amplification and 6th low pass filter. Then, this signal is entered in a digital value of digital signal processing(TMS320F2812) through the 16-bit A/D conversion. By doing so, the sound distance, direction and coordinate of bad insulator can be detected by realizing the correlation method of detecting the arriving time difference occurring on each microphone and the algorithm of detecting maximum time difference.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.233-238
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• 2015

In this paper, we proposed that immersive audio effect method using the effective noise to improve engagement in free-viewpoint TV(FTV) service. In the basketball court, we monitored the frequency spectrums by acquiring continuous audio data of players and referee using shotgun and wireless microphone. By analyzing this spectrum, in case that users zoomed in, we determined whether it is effective frequency or not. Therefore when users using FTV service zoom in toward the object, it is proposed that we need to utilize unnecessary noise instead of removing that. it will be able to be useful for an immersive audio implementation of FTV.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1023-1033
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• 2014

In this paper, performance improved hole-filling algorithm which includes the boundary noise removing pre-process that can be used for an arbitrary virtual view synthesis has been proposed. Boundary noise occurs due to the boundary mismatch between depth and texture images during the 3D warping process and it usually causes unusual defects in a generated virtual view. Common-hole is impossible to recover by using only a given original view as a reference and most of the conventional algorithms generate unnatural views that include constrained parts of the texture. To remove the boundary noise, we first find occlusion regions and expand these regions to the common-hole region in the synthesized view. Then, we fill the common-hole using the spiral weighted average algorithm and the gradient searching algorithm. The spiral weighted average algorithm keeps the boundary of each object well by using depth information and the gradient searching algorithm preserves the details. We tried to combine strong points of both the spiral weighted average algorithm and the gradient searching algorithm. We also tried to reduce the flickering defect that exists around the filled common-hole region by using a probability mask. The experimental results show that the proposed algorithm performs much better than the conventional algorithms.

• Journal of radiological science and technology
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• v.42 no.4
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• pp.285-290
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• 2019

Magnetic resonance imaging is a technique specialized in soft tissue imaging with high contrast resolution without in vivo ionization and has been widely used in various clinical settings. In particular, the recent increase in social stress factors has been used in the diagnosis of pituitary adenoma, the incidence increases rapidly. Recently, due to the development of magnetic resonance imaging, it is possible to diagnose micro pituitary adenoma, but despite the use of contrast medium, there has been a difficulty in diagnosing the pituitary adenoma due to its small size and noise. In order to solve this problem, a proposed method of separating signal components image and noise components image from a measured image is applied, and the improvement of diagnostic efficiency is attempted by removing noise. As a result, it was confirmed that the image quality was improved as a whole by applying SNR for 30 subjects data. It is expected that this study will be useful as a pre-processing method for improving the image quality and developing diagnostic indicators of pituitary adenoma.