• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.197-201
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• 2004

We describe a new edge detector based on the robust rank-order (RRO) test which is a useful alternative to Wilcoxon test, using $r{\times}r$ window for detecting edges of all possible orientations in noisy images. Some experiments of statistical edge detectors based on the Wilcoxon test and T test with our RRO detector are carried out on synthetic and real images corrupted by both Gaussian and impulse noise. We also implement these edge detectors using Java on the Web.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.329-332
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• 2009

Speckle noise reduction for ultrasound CT image using morphological adaptive median filtering based on edge preservation is presented in this paper. Speckle noise is multiplicative feature and causes ultrasound image to degrade widely from transducer. An input image is classified into edge region and homogeneous region in preprocessing. The speckle is reduced by morphological operation on the 2D gray scale by using convolution and correlation, and edges are preserved. The adaptive median is processed to reduce an impulse noise. As the result the proposed method enhances the image to about 20% in comparison with Winer filter by Edge Preservation Index and PSNR.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.394-400
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• 2019

Noise removal is one of the required step in processing digital video and there are many researches to develop algorithm that fits with its purpose and environment. However, present impulse noise removal methods are lacking in its function in terms of removing noise in edge and high frequency factors. Therefore, this research has Extended range of masks depending on density to determine noise so that high frequency factors can be preserved. The range of resolution is set based on median and standard deviation of inside resolution after removing impulse noise. afterwards, those resolution within the range are calculated by adding weight to have the final output value. The suggested algorithm has an enhanced function in removing noise in various areas with many edge and high frequency factors than present methods and their functions are compared through simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.750-753
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• 2007

According to the increase of demand for diverse multimedia services, techniques to use images as the tool of information transmission have been rapidly developed. However, impulse noise affecting the reception of image and signal error occurs in the process of digitalization and transmission of images. In order to remove this impulse noise, a nonlinear filter is generally applied and a standard median (SM) filter is representative. However, SM filter degrades the qualify of overall image by error of the edge component. Therefore, in this paper, to restore the corrupted image by impulse noise, a nonlinear spatial filter based on Min-max operation was proposed and was compared with conventional methods through simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.989-995
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• 2013

Image degradation caused by the impulse noise is generated in the process of image transmission and so on. It has been studied by many researchers in order to remove these noise. The representative impulse noise removal method includes SM filter. Though SM filter will indicate errors by the increasing of impulse noise density. Therefore, in this paper, in order to preserve the edges of the image, and reduce the distortion of the image, an improved adaptive median filter algorithm is proposed. In the simulation results, the algorithm showed excellent results in all several areas, and the PSNR is used as the criterion of evaluation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.918-920
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• 2011

In this paper, a simple edge pattern classification method is proposed for detecting straight line segments in an image corrupted by impulse noise. Corrupted images have complicated edge patterns. To detect straight line from an complicated edge pattern, it is needed to simplify the entire edge. The proposed algorithm separates the entire edge into 4 directional partial edge patterns. Each line segment is separated from the partial edge image where several line segments are overlapped, and then the straight line is detected. The results of the experiments emphasize that the proposed algorithm is simple but accurate.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1315-1318
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• 2004

Based on fuzzy 2-mean classification and template matching method, we propose a new algorithm to detect the edges of an image. In the algorithm, fuzzy 2-mean classification can classify all pixels in the mask into two clusters whatever the mask in the dark or light region; and template matching not only determines the edge's direction, but also thins the detected edge by a set of inference rules and, by the way, reduces the impulse noises.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.464-466
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• 1998

경계선 검출은 시각 인식 또는 기계 시각 인식의 과정에서 제일 먼저 수행되는 전처리 단계이다. 경계선 검출은 컴퓨터 시각 인식성능에 매우 중대한 요인으로 작용한다. 최근 MPEG-4에서 Model Based Coding 기법이 채택되면서, 경계선 검출 및 이를 이용한 컴퓨터 시각 인식의 중요성은 날로 커지고 있다. 한편, 잡음이 있는 영상의 경계선 검출 방법으로 여러 가지가 제시되었는데, 특히 잡음의 종류가 Additive White Gaussian인 경우에는 Canny Edge Detector가, Impulse인 경우에는 Dual Stack Filter를 적용한 방법이 각각 높은 성능으로 인정을 받고 있다. 그러나 Canny Edge Detector의 경우, Canny는 이론적인 Optimal Filter를 구하는 데에 성공하였지만 실제 적용에는, 이 Optimal Filter의 근사로써 Gauss함수의 1계 도함수를 사용하였다. 본 연구에서는 Gauss함수보다는 상당히 Optimal Filter와 가까운 Filter를 얻기 위하여 웨이블릿 변환을 사용한 Liao등의 방법과, 각기 다른 Scale에서의 웨이블릿 변환들이 가지는 잡음과의 관계를 고려한 새로운 경계선 검출방법을 개발하였다. 실험결과, 본 연구에서의 방법은 기존에 사용되던 Canny Edge Detector나 Stochastic Operator보다 뛰어난 성능을 보여주었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.463-466
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• 2008

With the development of Information Technology in recent years, the image has been an important means to store or express information. Generally, during the process of acquiring and storing images, the images can be corrupted by noise of which typical types are Impulse(Impulse Noise) and AWGN(Addiction White Gaussian Noise). Impulse noise shows irregularly in black and white over the length and breadth of the image by sharp and sudden disturbance of the image signal. In the Impulse noise environment, SM(Standard Median) filter would be used because of its good noise removal performance and simple algorithm. However, when SM filter removes noise, it also produces error at the edge of image and causes whole image quality deterioration. In this paper, we propose a method based on modified nonlinear filter operation scheme which enhances the features of noise removal and detail image preservation when restoring image in Impulse noise environment. And, we compared it with existing methods and the performances through simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.359-362
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• 2007

According to the development of information and communication technology, a great deal of researches have been taken in image digital processing field. And for earning the standard level of images, to remove noises such as impulse noise has became a essential demand. In those algorithms which remove impulse noise effectively, the standard median (SM) filter is representative. However, it has a disadvantage to degrade the quality of overall image by occurring errors in the edge domain. Therefore, in this paper, to restore the corrupted image by impulse noise, a nonlinear spatial filter based on Min-max operation was proposed and it was compared with conventional methods through simulations.