• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1725-1731
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• 2013

Recently, as industrial society is developed as high digital information age, image processing is used in a variety of areas. However, image deterioration is still occurred by several noises in the data processing, and different kinds of researches are in progress for noise removal. Therefore, this paper limited the modified median filter by using standard deviation to removes impulse noise. The proposed algorithms divided into noise detection and noise removal, the noise free pixel is maintained, the noise pixel filtered. And it was compared with the existing methods for its objective judgment, using PSNR(peak signal to noise ratio) as standard criteria.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.676-678
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• 2016

Noise occurs in the process of obtaining, transmission, and processing in image processing systems and these noises lower the resolution of image and cause visual errors. Currently, a representative filter to remove salt and pepper noise is SMF(standard median filter) but it is inadequate in preserving edge as the noise field expands. Therefore, for salt and pepper noise enviroment, the study suggested and algorithm that are places with original pixel when the central pixel is non-noise and process by applying weighted value on areas with less local mask pixel changes when there is noise.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.346-349
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• 2017

Digital image processing is widely used in a variety of areas, and noise elimination is used as the preprocessing in all the image processing processes. Degradation is occurred in the image data due to multiple reasons. Degradation is to add the noise in the image signal, and salt and pepper noise is the representative one to cause degradation. Therefore, image restoration algorithm was proposed to process with histogram weight filter and median filter by the noise density of local mask to restore the damaged image in the salt and pepper noise environment, in this article. In addition, it was compared with the existing methods using peak signal to noise ratio(PSNR) as the objective determination factor of improvement effect.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2265-2271
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• 2014

In modern society digital equipments that are related with various hardware and software are popularized, and digital images are widely applied in the field of production and scientific research. In general, however, images are degraded by the noise in the process of transmission and storage. In this paper, to reduce the influence of mixed noises, the algorithm in which noises in the space area are classified into impulse noise and Gaussian noise and this is processed by applying weighted value, while that is processed by modified nonlinear filter is proposed. And the excellence of the proposed algorithm is judged by PSNR(peak signal to noise ratio).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2029-2036
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• 2017

Currently, the demand for multimedia services is increasing with the rapid development of the digital age. Image data is corrupted by various noises and typical noise is mainly AWGN, salt and pepper noise and the complex noise that these two noises are mixed. Therefore, in this paper, the noise is processed by classifying AWGN and salt and pepper noise through noise judgment. In the case of AWGN, the outputs of spatial weighted filter and pixel change weighted filter are composed and processed, and the composite weights are applied differently according to the standard deviation of the local mask. In the case of salt and pepper noise, cubic spline interpolation and local histogram weighted filters are composed and processed. This study suggested the multiple image restoration filter algorithm which is processed by applying different composite weights according to the salt and pepper noise density of the local mask.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.253-255
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• 2022

Thanks to the 4th industrial revolution and the development of various communication media, technologies such as artificial intelligence and automation are being grafted into industrial sites in various fields, and accordingly, the importance of data processing is increasing. Image noise removal is a pre-processing process for image processing, and is mainly used in fields requiring high-level image processing technology. Various studies have been conducted to remove noise, but various problems arise in the process of noise removal, such as image detail preservation, texture restoration, and noise removal in a special area. In this paper, we propose a switching mask filter based on the noise intensity to preserve the detailed image information during the impulse noise removal process. The proposed filter algorithm obtains the final output by switching to the extended mask when it is determined that the density is higher than the reference value when noise is determined in the area designated as the filtering mask. Simulation was conducted to evaluate the performance of the proposed algorithm, and the performance was analyzed compared to the existing method.

• 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 IEEK Conference
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• 2001.09a
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• pp.543-546
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• 2001

영상에 포함된 잡음은 시각적인 문제를 일으킬 뿐만 아니라, MPEG이나 H.263과 같은 영상 압축 시스템의 부호화 효율을 떨어뜨린다. 따라서 영상 압축 시스템의 입력으로 이러한 잡음이 포함된 신호가 들어갈 때, 잡음 제거 필터를 사용하여 잡음을 제거한 후 영상 압축을 하는 것이 시각적인 면에서나 압축 효율적인 면에서 매우 효과적이다. 본 논문에서는 이웃한 4개의 화소값을 참조하여 잡음의 존재 여부를 판단하고, 판단 결과를 이용하여 선택적으로 잡음을 제거하는 적응형 십자형 중간값(median) 필터를 제안한다. 제안된 방법을 이용하면 전체 영상에 걸쳐 필터를 이용하는 방법에 비해 계산량이 크게 줄고, 영상의 필터 처리후에 나타나는 뭉개짐(blurring) 현상을 줄일 수 있다. 또한 잡음이 처리된 영상을 시간방향으로 Look-up Table에 따른 IIR필터를 통과시킴으로써 시간상으로 존재하는 잡음을 제거하여 동영상의 주관적 화질을 향상시킬 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.683-686
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• 2010

본 논문은 영상 내에서 영역을 분할하여 영상 잡음을 효과적으로 제거하는 기법을 제안한다. 제안한 방법을 통해 잡음 영상을 영역 분할 경우 잡음부분까지 영역 분할되는 문제가 발생하기 때문에 잡음 영상을 저대역(Low-pass) 필터를 통과함으로써 잡음을 최소화한다. 저대역 필터를 통과한 영상에서 에지를 추출하여 비정상적인 에지의 추출을 방지함으로써 영상이 가진 근본적인 에지를 정확하게 추출한다. 획득한 에지 정보를 바탕으로 각 영역간의 히스토그램의 평균 오차를 이용하여 영역을 분할한다. 분할된 영역은 각 영역별로 저대역(Low-pass) 필터를 통과시킴으로써 영역에 맞는 잡음 제거를 통해서 더욱 빠르고 효과적으로 제거한다. 본 논문의 방법은 기존의 학습을 통한 잡음 제거 방법과 다르게 학습 시간이 요구되지 않으며, Non-local Means의 방법과 다르게 큰 연산량을 요구하지 않기 때문에 유사한 성능으로 빠른 잡음 제거를 할 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.53-54
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• 2010

본 논문에서는 단일 채널 디지털 오디오 신호에서 스펙트로그램과 영상 처리 기법을 이용하여 크래클 잡음을 검출하는 알고리즘을 제안한다. 오디오 신호의 주파수 특성을 효율적으로 분석하기 위해 스펙트로그램을 특정 컬러맵을 이용하여 컬러 영상으로 변환한 후 영상 처리 기법을 적용하여 크래클 잡음이 존재하는 구간을 검출하여 디지털 오디오 복원에 이용한다. 특히 고전영화에 나타나는 크래클 잡음은 에너지와 신호 길이가 음성이나 음악 신호와 유사하여 기존의 스펙트럴 음성 검출 기법으로는 검출에 어려움이 있다. 이에 비해 스펙트로그램 영상에서는 크래클 잡음이 다른 신호들과 구분되는 특성을 나타내므로 영상 처리 기법을 적용하여 경계 검출과 Hough 변환에 의한 선 검출을 이용하여 크래클 잡음을 검출한다. 제안된 알고리즘은 고전 영화 디지털 오디오 복원에 적용하였으며 크래클 잡음 검출에 우수한 성능을 보여준다.