• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.2
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• pp.183-190
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• 2013

In this paper, we propose a spatially adaptive noise detection and removal algorithm for a single degraded image. Under the assumption that an observed image is Gaussian-distributed, the noise information is estimated by local statistics of degraded image, and the degree of the additive noise is detected by the local statistics of the estimated noise. In addition, we describe a noise removal method taking a modified Gaussian filter which is adaptively determined by filter parameters and window size. The experimental results demonstrate the capability of the proposed algorithm.

• Journal of IKEEE
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• v.3 no.1 s.4
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• pp.133-140
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• 1999

When the current optical communication system is used for the DWDM, it raise the serious interference because an interval between the adjacent channels is narrow. The FBG filter for the DWDM is able to reduce the interferences between the adjacent channels. In this paper, therefore, we find the reflection spectrums for the three types of induced index changes, that is, uniform, Gaussian apodized, and raised-cosine apodized. From the obtained results in this paper, we can see that uniform FBG does not fit, and that the smaller the maximum induced index change ${\sigma}$ is and the larger the value of parameter C in the raised-cosine apodized FBG and G in the Gaussian apodized FBG are, the fitter they are on the narrow filter for DWDM. But, we can also see that the raised-cosine apodized FBG has more excellent property than the Gaussian apodized FBG because it has the narrower maximum reflection spectrum band and the lower sidelobes than the other.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.175-182
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• 2017

Noises are usually generated by various external causes and low quality devices in image data acquisition and recording as well as by channel interference in image transmission. Since these noise signals result in the loss of information, subsequent image processing is subject to the corruption of the original image. In general, image processing is performed in the mixed noise environment where common types of noise, known to be Gaussian and impulse, are present. This study proposes an iterative weighted mean filter for reducing mixed type of noise. Impulse noise pixels are first turned off in the input image, then $3{\times}3$ sliding window regions are processed by replacing center pixel with the result of weighted mean mask operation. This filtering processes are iterated until all the impulse noise pixels are replaced. Applied to images corrupted by Gaussian noise with ${\sigma}=10$ and different levels of impulse noise, the proposed filtering method improved the PSNR by up to 12.98 dB, 1.97 dB, 1.97 dB respectively, compared to SAWF, AWMF, MMF when impulse noise desities are less than 60%.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.31-39
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• 2010

The paper proposes the median filter based Retinex algorithm to detect the lanes in a foggy image. Whether an input image is foggy or not is determined by analyzing the histogram in the pre-defined ROI(Region of Interest). If the image is determined as a foggy one, then it is improved by the median filter based Retinex algorithm. By replacing the Gaussian filter by the median filter in the Retinex algorithm, the processing time can be reduced and the lane features can be detected more robustly. Once the enhanced image is acquired, the binarization based on multi-threshold and the labeling operations are applied. Finally, it detects the lane information using the size and direction parameters of the detected lane features. The proposed algorithm has been evaluated by using various foggy images collected on different road conditions to prove that it detects lanes more robustly in most cases than the conventional methods.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.125-131
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• 2019

Through the 4th Industrial Revolution, various digital equipments are being distributed, and accordingly, the importance of data processing is increasing. As data processing has a great effect on the reliability of equipment, its importance is increasing, and various studies are being conducted. In this paper, we propose an algorithm to remove AWGN in consideration of the noise in the image. The proposed algorithm is used in the filtering process by inferring the standard deviation of the image noise. The noise is removed by dividing the filter for the high frequency component and the filter for the low frequency component compared with the standard deviation of the filtering mask. The proposed algorithm is simulated with the existing methods for evaluation and compared and analyzed by difference image, PSNR and profile. The proposed algorithm minimizes the effect of noise and preserves the important characteristics of the image and shows the performance of efficient noise removal.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.11-13
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• 2011

양방향 필터 (Bilateral filter)는 에지 보전 평활화 필터로써 디노이징, 반사 제거, 스테레오 매칭 등 다양한 분야에서 사용되고 있다. 이는 기존의 가우시안 필터에 사용되는 공간 도메인 커널 (spatial kernel)이외에 강도 도메인 커널 (range kernel)을 추가로 사용하여 비슷한 강도의 픽셀에 높은 가중치를 부여함으로써 에지를 보전하면서 평활화를 한다. 또한 양방향 필터는 비등방성 확산 필터 (Anisotropic diffusion filter)와 달리 항상 수렴을 보장한다. 따라서 본 논문에서는 고정점 반복 이론을 적용하여 양방향 필터의 수렴을 수학적으로 증명한다.

• Journal of Korea Multimedia Society
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• v.12 no.1
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• pp.26-30
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• 2009

We propose an adaptive Recursive Least Rank(RLR) L-filter which uses an L-estimator in order statistics and is based on rank estimate in robust statistics. The proposed RLR L-filter is a non-linear adaptive filter using non-linear adaptive algorithm and adapts itself to optimal filter in the sense of least dispersion measure of errors with non-homogeneous step size. Therefore the filter may be suitable for applications when the transmission channel is nonlinear channels such as Gaussian noise or impulsive noise, or when the signal is non-stationary such as image signal.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.409-412
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• 2011

본 논문에서는 흉부 X선 영상으로부터 폐 종류 음영을 검출하기 위한 필터를 예측해서 바람직하게 평가하기 위한 방법을 제안한다. 더욱이 그 평가방법을 이용해서 이전부터 제안한 다중해상도 라플라시안-가우시안 필터의 평가를 행한다. 전문의의 진단보조 혹은 종합자동진단시스템의 구성요소로서 필터가 행하는 역할을 고려한 후에 필터가 만족해야할 조건 및 그 조건을 만족한 경우에 있어서 몇가지 성능평가 척도를 명확히 한다. 제안한 평가방법을 통해서 다중해상도 필터가 단일해상도 필터에 비해 높은 성능을 갖게됨을 명확히 한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.23-30
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• 2011

In the wireless sensor network(WSN), the detection of precise location of sensor nodes is essential for efficiently utilizing the sensing data acquired from sensor nodes. Among various location methods, the received signal strength (RSS) based localization scheme is mostly preferable in many applications since it can be easily implemented without any additional hardware cost. Since the RSS localization method is mainly effected by radio channel between two nodes, outlier data can be included in the received signal strength measurement specially when some obstacles move around the link between nodes. The outlier data can have bad effect on estimating the distance between two nodes such that it can cause location errors. In this paper, we propose a RSS-based localization method using Robust Statistic and Gaussian filter algorithm for enhancing the accuracy of RSS-based localization. In the proposed algorithm, the outlier data can be eliminated from samples by using the Robust Statistics as well as the Gaussian filter such that the accuracy of localization can be achieved. Through simulation, it is shown that the proposed algorithm can increase the accuracy of localization and is more robust to non gaussian noise channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1264-1270
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• 1992

MF(Morphological filter) is generally composed of several morphological operation, which are the diverse structuring element. The two basic operation are erosion and dilation. The two other operation, opening and closing, are defined based on these two operation. Performance of open-closing(OC) is better exellent than close-opening(CO) to reduce noise of image data with Gaussian noise. In this paper, to use the hybrid median filter in processing the image, is shown that hybrid median filter has better results image quality than other filters, to analyze by computer simulation.