• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.9B
• /
• pp.1731-1741
• /
• 1999

Color images are often corrupted by the noise due to noisy sensors or channel transmission errors. Some filters such as vector media and vector $\alpha$-trimmed mean filter have bee used for color noise removal. In this paper, We propose the fuzzy cluster filters based on the possibilistic c-means clustering, because the possibilistic c-means clustering can get robust memberships in noisy environments. Also, we propose weighted vector $\alpha$-trimmed mean filter to improve the conventional vector $\alpha$-trimmed mean filter. In this filter, the central data are more weighted than the outlying data. In this paper, we implemented the color noise generator to evaluate the performance of the proposed filters in the color noise environments. The NCD measure and visual measure by human observer are used for evaluation the performance of the proposed filters. In the experiment, proposed fuzzy cluster filters in the sense of NCD measure gave the best performance over conventional filters in the mixed noise. Simulation results showed that proposed weighted vector $\alpha$-trimmed mean filters better than the conventional vector $\alpha$-trimmed mean filter in any kinds of noise.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.7
• /
• pp.1393-1398
• /
• 2004

Image is degraded by several causes such as the process of acquisition, storage and transmission. To restore those images, many researches have been continued. Centrally methods to restore degraded image by AWGN(additive white gaussian noise) a.e mean filter and wiener filter. Especially, mean filter is superior in noise reduction of area that is a small change of luminosity. But mean filter brings about the effect smoothing edge components of the image, because it does'nt consider characteristics of the image. So in this paper we propose an image restoration method compounding respective images adding established weights, after filtering with mean filter and powerful wiener filter in both improvement of contrast and preservation of edge components.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.12
• /
• pp.3718-3726
• /
• 1999

Color image is more effective than gray one in human visual perception. Therefore, color image processing becomes important area. Color images are often corrupted by noises due to the input sensor, channel transmission errors and so on. Some filtering techniques such as vector median, mean filter, and vector $\alpha-trimmed$ mean filter have been used for color noise removal. Among them, vector $\alpha-trimmed$ mean filter gave the best performance in the mixed color noise. But, there are edge shift and blurring effect because vector $\alpha-trimmed$ mean filter is uniformly processed across the image. So, we proposed a conditional fuzzy cluster filter to improve this problems. Simulation results showed that the proposed scheme improves the NCD measure and visual quality over the conventional vector $\alpha-trimmed$ mean filter in the mixed color noise.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.1413-1415
• /
• 2015

본 논문에서 우리는 의상영역의 유사성을 검사 시 색상분석에 있어 정확도를 향상시키기 위해 Bilateral 필터와 Mean-Shift 알고리즘을 적용하였다. 본 연구의 평가부분에서 필터를 적용한 영상이 의상영역의 구김이나 빛에 의한 영향이 필터를 적용하지 않은 영상보다 적다는 것을 실험을 통해 증명한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.05a
• /
• pp.407-410
• /
• 2009

본 논문에서는 개선된 mean shift를 이용한 컬러 영상 분할을 소개한다. Mean shift는 Yizong Cheng에 의해 재조명되고 Dorin Comaniciu 등에 의해 정리되어 영상 필터링(image filtering), 영상 분할(image segmentation), 물체 추적(object tracking) 등 여러 응용 분야에 널리 활용되고 있다. 커널을 이용해 밀도를 추정하고 밀도가 가장 높은 점으로 커널을 연속적으로 이동함으로써 지역적으로 주요한 위치로 데이터 값을 갱신시킨다. 그러나 영상에 포함된 모든 화소에 대해 mean shift를 수행해야하기 때문에 연산 시간이 많이 소요되는 단점이 있다. 본 논문에서는 mean shift 필터링 과정을 분석하고 참조수렴방법과 강제수렴방법을 이용해 소요 시간을 단축시켰다. 모든 점에 대해 mean shift를 수행하는 대신 특정 조건을 만족하는 픽셀은 이웃 픽셀의 수렴 값을 참조하고, mean shift 과정에 진동 또는 미미한 이동을 계속하는 픽셀은 강제 수렴을 실시하였다. 개선된 방법과 기존의 mean shift 방식을 적용하여 영상 필터링과 영상 분할에 적용한 실험에서 결과 영상에는 차이가 적고 기존의 방법에 비해 수행 시간이 24% 정도 소요됨을 확인하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.393-396
• /
• 2010

In this paper the process of transmitting images signal restore to image corrupted by impulse noise proposed alpha-trimmed mean filter. the proposed filter first identifies the noise pixels using the morphological noise detector and then removes the detected impulse noise using the alpha-trimmed mean filter. these proposed filter can realize the accurate noise detection and it can remove impulse noise effectively while preserving edge region in the image very well. Through the simulation, we compared with the existing methods and capabilties.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.7
• /
• pp.81-89
• /
• 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 Broadcast Engineering
• /
• v.17 no.6
• /
• pp.1048-1060
• /
• 2012

In this paper, an adaptive temporal and spatial filter (ATSF) based on mean square error (MSE) estimation is proposed. ATSF is a block based de-noising algorithm. Each noisy block is selectively filtered by a temporal filter or a spatial filter. Multi-hypothesis motion compensated filter (MHMCF) and bilateral filter are chosen as the temporal filter and the spatial filter, respectively. Although there is no original video, we mathematically derivate a formular to estimate the real MSE between a block de-noised by MHMCF and its original block and a linear model is proposed to estimate the real MSE between a block de-noised by bilateral filter and its original block. Finally, each noisy block is processed by the filter with a smaller estimated MSE. Simulation results show that our proposed algorithm achieves substantial improvements in terms of both visual quality and PSNR as compared with the conventional de-noising algorithms.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.4
• /
• pp.625-632
• /
• 2021

This paper studies the effect of the number of filters in the CNN (Convolutional Neural Network) layer on the performance of a noise attenuator. Speech is estimated from a noised speech signal using a 64-neuron, 16-kernel CNN filter and an error back-propagation algorithm. In this study, in order to verify the performance of the noise attenuator with respect to the number of filters, a program using Keras library was written and simulation was performed. As a result of simulation, it can be seen that this system has the smallest MSE (Mean Squared Error) and MAE (Mean Absolute Error) values when the number of filters is 16, and the performance is the lowest when there are 4 filters. And when there are more than 8 filters, it was shown that the MSE and MAE values do not differ significantly depending on the number of filters. From these results, it can be seen that about 8 or more filters must be used to express the characteristics of the speech signal.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.557-560
• /
• 2001

본 논문에서는 시공간 3차원 잡음 제거기의 ASIC 설계 및 구현결과를 소개한다. 구현된 잡음 제거기는 휘도와 색차신호에 대한 잡음제거 필터들로 구성된다. 휘도에 적용한 필터는 A-MEAN 필터와 A-LMMSE 필터를 결합한 형태의 필터를 시공간적으로 연결한 필터로써, 특히 시간방향으로 IIR 필터 형태를 갖도록 설계하여 평탄한 영상영역에서 보다 강한 잡음 제거 효과를 갖도록 하였다. 한편, 색차신호에 대해서는 5탭 길이를 갖는 1차원 A-MEAN 필터를 적용하였다. C-언어를 이용한 시뮬레이션을 통해 설계된 잡음 제거기의 성능을 평가하였고, VHDL과 C-언어에 의한 시뮬레이션 결과를 비교하여 VHDL-코드의 검증을 수행했다. 구현과정은 시뮬레이션과 논리합성 등 전반부 설계를 Synopsys 툴을 이용하여 수행했고, 레이아웃 등 후반부 설계를 Cadence 툴과 Apollo 툴을 이용하여 수행했다.