• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.371-374
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• 2001

본 논문에서는 움직임 보상을 이용한 Motion-Adaptive De-interlacing Method를 제안 한다. 정확한 움직임 추정을 위해서 Pre-filter로서 EBMF(Edge Based Median Filter)를 사용하며 새로운 Block Matching Method를 제안한다. Temporal Filter로서 Motion Missing Error를 제거하기 위해 입력 영상의 움직임 영역에 따라 각각 다른 임계 값을 적용하는 AMPDF(Adaptive Minimum Pixel Difference Filter)를 적용하였으며 MMD(Maximum Motion Detection)와 SAD(Sum of Difference)를 이용하여 빠른 움직임 영역에서 화질을 향상시켰다. 최종적으로 잘못된 움직임 보상에 기인하는 화질의 열화를 방지하기 위한 Motion Correction Filter를 제안한다.

• ETRI Journal
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• v.34 no.4
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• pp.564-571
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• 2012

This paper presents an algorithm for removing high-density impulsive noise that generates some serious distortions in edge regions of an image. Although many works have been presented to reduce edge distortions, these existing methods cannot sufficiently restore distorted edges in images with large amounts of impulsive noise. To solve this problem, this paper proposes a method using connected lines extracted from a binarized image, which segments an image into uniform and edge regions. For uniform regions, the existing simple adaptive median filter is applied to remove impulsive noise, and, for edge regions, a prediction filter and a line-weighted median filter using the connected lines are proposed. Simulation results show that the proposed method provides much better performance in restoring distorted edges than existing methods provide. When noise content is more than 20 percent, existing algorithms result in severe edge distortions, while the proposed algorithm can reconstruct edge regions similar to those of the original image.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.6
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• pp.65-71
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• 2017

Digital images and videos are subject to various types of noise during storage and transmission. Among these noises, Salt & Pepper noise degrades the compression efficiency of the original data and causing deterioration of performance in edge detection or segmentation used in an image processing method. In order to mitigate this noise, there are many filters such as Median Filter, Weighted Median Filter, Center Weighted Median Filter, Switching Weighted Median Filter and Adaptive Median Filter. However these methods are inferior in performance at high noise density. In this paper we propose a new type of filter for noise mitigation in wireless communication environment where Salt & Pepper noise occurs. The proposed filter detects the location of the damaged pixel by Salt & Pepper noise detection and mitigates the noise by using adjacent pixel values which are not damaged in a certain area. Among the proposed filters, the performance of the filter using the $3{\times}3$ error mask is compared with that of the conventional methods and it is confirmed that when density of noise in the image is 95%, their performances are improved as 13.24 dB compared to MF and 13.09 dB compared to AMF.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.535-538
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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 to preserve edges. As the result, MAM of the proposed method enhances the image to about 10% in comparison with Winner filter by Edge Preservation Index and PSNR, and 10% to only adaptive median filtering.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.81-89
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• 1999

Image obtained by incomplete communication always include noise, blur and distortion, etc. In this paper, we propose and apply the new spatial filter algorithm, called an optimal adaptive generalized stack filter(AGSF), which optimizes adaptive generalized stack filter(AGSF) using neural network weight learning algorithm of back-propagation learning algorithm for improving noise removal and edge preservation rate. AGSF divides into two parts: generalized stack filter(GSF) and adaptive multistage median filter(AMMF), GSF improves the ability of stack filter algorithm and AMMF proposes the improved algorithm for reserving the sharp edge. Applied to neural network theory, the proposed algorithm improves the performance of the AGSF using two weight learning algorithms, such as the least mean absolute(LAM) and least mean square (LMS) algorithms. Simulation results of the proposed filter algorithm are presented and discussed.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.5
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• pp.863-867
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• 1987

When digital image signals are transmitted or stored, they may be usually degraded by impulsive noise such as BSC noise. Though median filtering is a very effective method to reduce the impulsive noise, it brings non-negligible distortion after filtering. Several algorithms have been proposed to reduce such a distortion, but their reconstructed image quality are inadequate in some cases and they have a difficulty in real-time processing. In this paper, an effective filtering algorithm which can not only reduce the noise effectively but also preserve the edges well and lessen the distortion greatly, is presented. The proposed algorithm is an adaptive algorithm of median filter using local statistics, based on the characteristics of human eyes. The adaptive algorithm results shwo performance improvement of up to 3-4 dB over the nonadaptive one.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.77-77
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• 2001

MMMF(Modified 2D Multi-shell Median Filter)를 기초로 하여 가변 문턱 조건과 홀/짝수 다중셀을 이용한 Adaptive Odd/Even MMF(Multi-shell Median Filter)를 제안하였다. 제안된 알고리즘은 MATLAB을 이용하여 연구하고 테스트하였다. 제안된 알고리즘의 성능은 이미 잘 알려진 이미지에 임펄스 노이즈(Impulse Noise)와 Line Missing을 적용하여 평가하였고 이를 FPGA로 구현하였다. 제안된 가변 문턱 조건은 연산 시간과 불필요한 재배치를 줄였고, 홀수 셀과 짝수 셀은 각각 십자 방향과 대각선 방향의 Line Missing을 복구하였다. 특히 짧은 연산 시간으로 실시간을 요구하는 이미지 처리 분야에서 효과적으로 이용할 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.237-243
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• 2015

In recent image processing, active researches have been made along with rapid development in digital times. However, it is know that the image degradation occurs due to various external factors in the processes of image data processing, transmission and storage, and the main reason of image degradation is due to the noise. Typical methods to remove the noise are CWMF(center weighted median filter), A-TMF(alpha-trimmed mean filter) and AWMF(adaptive weighted median filter) and these methods have a little bit lacking noise reduction characteristics in mixed noise environments. Therefore, in order to remove the mixed noise, image restoration filter processing algorithm was suggested in this paper which processes by applying the median value of the mask and space weighted value after noise judgment. And for the objective judgment, it was compared with existing methods and PSNR(peak signal to noise ratio) was used as a judgment standard.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.556-566
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• 2001

This paper proposes a motion-adaptive de-interlacing algorithm based on EBMF(Edge Based Median Filter) and AMPDF(Adaptive Minimum Pixel Difference Fillet). To compensate 'motion missing'error, which is an important factor in motion-adaptive methods, we used AMPDF which estimates an accurate value using different thresholds after classifying the input image to 4 classes. To efficiently interpolate the moving diagonal edge, we also used EBMF which selects a candidate pixel according to the edge information. Finally, we, to increase the performance, adopted an adaptive interpolation after classifying the input image to moving region, stationary region, and boundary region. Simulation results showed that the proposed method provides better performance than the existing methods.