• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.484-486
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• 2018

Recently, with the increase in use of digital equipment in various fields, the importance of image and signal processing is increasing. However, many types of noise are generated during transmission and reception of digital signal, causing errors. For this reason, noise removal is mandatorily performed during pre-processing phase in many fields. In the present paper, noise is classified through noise evaluation, and noise removal is performed to remove impulse noise and noise with AWGN-added noise. And, proposed is an algorithm which utilizes modified Gaussian filter and directional effective pixels according to noise type. Simulation results show superior noise-removal characteristics, and for objective evaluation, compared with conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1284-1289
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• 2016

Recently, digital image processing is applied a lot to the broadcasting, communication, computer graphic, and medical sectors. It generates noise when data is transmitted. There are many kinds of noises that add to the image such as salt and pepper noise, AWGN, and complex noise. Thus, this study divides the corrupted image into four4 areas and estimates the types of noises each pixel, and this study suggested a switching filter that separates the estimated into salt and pepper noise and AWGN. In the case that center pixel of local mask is corrupted by salt and pepper noise, it used a histogram probability weighting of subdivided area. Also, in case that it is corrupted by AWGN, algorithm that is applied to with different weights given for the distribution of each area with using subdivided area's distribution was suggested. For an objective comparison and conclusion, this study used PSNR and compared to existing methods.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.961-964
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• 2009

본 논문은 복합재료로부터 얻어진 C-scan영상에서의 효과적인 잡음 제거에 관한 연구 내용이다. 복합재료에서의 결함을 검출하는 것은 여러 실용, 응용분야에서 관심을 가지는 주제이다. 초음파 영상은 대부분이 육안으로 정확한 판단을 하기에는 어렵고, 잡음의 영향으로 정확한 결함에 대한 영역을 파악하는데 문제를 발생시킨다. 결함의 정확한 판별을 위해서는 물체의 영역을 정확히 판별하는 것이 중요하지만 영상에서 잡음에 대한 문제를 우선 해결해야 한다. C-scan 영상에서의 배경과 결함의 경계영역을 보존하면서 잡음 제거를 위해 웨이브렛(Wavelet) 변환을 이용하는 방법을 제안한다. 특히, C-scan 영상에서 Filtering을 적용하는데에 있어 드비시(Daubechies) Wavelet Filtering이 결함영역에 대한 좀 더 명확한 분석이 가능하게 함을 얘기하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.209-212
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• 2007

Digital images are corrupted by noises, during signal acquisition and transmission. Amount those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. The conventional image restoration algorithms are mostly taken in simple noise environment, but they didn't perform very well in tempter noises environment. So a modified image restoration algorithm, which can remove complex noises by using the intensity differences and spatial distances between center pixel and its neighbor pixels as parameters, is proposed in this paper. Simulation results demonstrate that the proposed algorithm can't only remove AWGN and impulse noise separately, but also performs well in preserving details of images as edge.

• The Journal of the Acoustical Society of Korea
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• v.15 no.4
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• pp.70-76
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• 1996

In the case of an image corrupted with mixed noise, conventional MMSE filter can not remove such a mixed noise properly, because the impulse moise cause a certain bias of the minimum mean-square error estimate at regions close to outliers. In this paper, we proposed the new method or removal of mixed noise by combining MMSE filtering structure with local multi-windowing method according to directions and with ranked-order method. As a result, the improvement of the image quality with the proposed was obtained between about 9.7 and 35.2 times in the sense of NMSE(normalized mean square errors) evaluation than that of MMSE filter. Also, we could obtain the enhanced image in the mixed noisy image from visual and quantitative aspect.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.629-635
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• 2017

In this paper, we proposed a nonlinear synthesis filter for noise reduction to reduce the effects of Gaussian noise and impulse noise. When the centralization of the local mask is judged to be Gaussian noise by the noise judgment, the weight value of the weight filter are applied differently according to the spatial weight filter and the pixel change by using the sample variance in the local mask. And if it is determined as the impulse noise, we proposed an algorithm that applies different weights of local histogram weight filter and standard median filter according to noise density of mask. In order to evaluate the performance of the proposed filter algorithm, we used PSNR(peak signal to noise ratio) and compared existing methods and proposed filter algorithm in the mixed noise environment with Gaussian noise, impulsive noise, and two noises mixed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.210-212
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• 2021

In modern society, various digital equipment are being distributed due to the influence of the 4th industrial revolution, and they are used in a wide range of fields such as automated processes, intelligent CCTV, medical industry, robots, and drones. Accordingly, the importance of the preprocessing process in a system operating based on an image is increasing, and an algorithm for effectively reconstructing an image is drawing attention. In this paper, we propose a filter algorithm based on a combined weight value to reconstruct an image in a complex noise environment. The proposed algorithm calculates the weight according to the spatial distance and the weight according to the difference between the pixel values for the input image and the pixel values inside the filtering mask, respectively. The final output was filtered by applying the join weights calculated based on the two weights to the mask. In order to verify the performance of the proposed algorithm, we simulated it by comparing it with the existing filter algorithm.

• Journal of Advanced Navigation Technology
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• v.6 no.2
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• pp.151-157
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• 2002

This paper has investigated the PER performance and the packet throughput of Bluetooth multi-piconet in the presence of impulsive noise, Rician fading, and co-channel interference. Specially, it is simulated the effect of co-channel interference in Bluetooth multi-piconet. From the simulation results, it is obtained that the co-channel interference due to multi-piconet and impulsive noise affects performance of Bluetooth multi-piconet. And, we have known that the SAW-ARQ method is very efficient to improve the performance of Bluetooth packet transmission.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.11
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• pp.1125-1131
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• 1991

In a generalized model with which we can represent multiplicative noise as well as purely additive noise, we consider detection of composite signals which contain both deterministic and stochastic signal components. To illustrate the performance of the locally optimum detectors, finite sample-size performance characteristics are obtained and compared with those of other detectors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.779-781
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• 2013

As the demand for various multimedia service increases the technology that utilizes image as information transfer method develops rapidly. Though average filter, median filter and weight filter etc. have been proposed to remove various noises that are added to images, the existing methods are short of noise removal and edge reservation performance. Therefore, in this paper an algorithm, in which noise is decided at the first hand, and then it is processed through modified median filter and adaptive weighted average filter, is proposed to effectively remove the complex noise that has been added to an image. And it was compared with existing methods through simulation and PSNR(peak signal to noise ratio) has been used as a criterion.