• International Journal of Contents
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• v.5 no.4
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• pp.7-12
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• 2009

In this paper, the authors showed that the removal of impulse noise in CR images was implemented using variety of median filters and SNR/PSNR measurements. They used three kinds of medical images-hand, skull, and knee- for experimental results. But the noise in CR image was only the impulse noise. In real medical image, the noise of an image would be very different type. Therefore. the lack of experimental results using different noise in CR images is one flaw.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.165-170
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• 2019

Recently, modern society has come up with the importance of video processing as various imaging systems have developed. However, deterioration occurs in the process of transmitting, processing, and storing video data for various reasons. Deterioration will damage the original image, and the typical noise is Salt and Pepper noise. There are A-TMF, CWMF, and linear interpolation as the means to eliminate Salt and Pepper noise. However, these methods show somewhat poor noise abatement performance in high-density noise areas. Therefore, this paper proposes an algorithm to eliminate noise using modified linear interpolation. To prove the validity of the proposed algorithm, PSNR, Profile was used to compare it with existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.254-260
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• 2019

Recently, the importance of signal processing has become gradually significant, as the frequency of video media increases in various fields. However, numerous kinds of noise generated in the transmission and reception processes can possibly affect the signal information, and the noise removal is for that reason essential as a preprocessing step. In this paper, we propose an algorithm to remove the mixed noise which is composed of impulse noise and AWGN. This algorithm is used for image restoration by noise judgment for efficient noise removal in a complex noise environment, and the noise is removed by considering spatial characteristics and pixel variations. Simulation results show that unlike existing methods, the algorithm has excellent noise cancellation characteristics by minimizing both noise effects and consequently eliminating the mixed noise; for objective judgment, we compared and analyzed the data using PSNR and profile.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.795-797
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• 2014

Image treatment has grown in its necessity in many fields due to the development of display technology used in smart phones and tablet computers. In digital imaging technology, noise is created by many causes during the process of acquiring, transmitting and treating image data. Therefore, this paper suggests a median filter that is more competent in removing noise by taking into account the direction when restoring noisy images that have been damaged by impulse noise. In order to verify the noise removal characteristics, PSNR(peak signal to noise ratio) was used for comparison against existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1167-1173
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• 2017

As the society increasingly embraces the high - tech digital information age, the field of image processing becomes progressively more branched out and becoming an imperative field. However, image data is deteriorated due to various causes during transmission and salt and pepper noise is typical. Typical methods for removing salt and pepper noise include CWMF, SWMF, and A-TMF. However, existing methods are somewhat insufficient in their ability to remove noise in salt and pepper noise environments. Therefore, in this paper, after it is determined whether noise removal is needed, the following measures were taken. If the center pixel was non-noise, the original pixel was preserved, If it was noise, we proposed a two - dimensional spline interpolation method and a median filter depending on the noise density of the local mask. For the purpose of objective judgment, we compared the results with that of existing methods and used PSNR (peak signal to noise ratio) as a judgment criterion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.255-257
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• 2018

Recently, as the frequency of use of video media increases in various fields, the importance of signal processing is increasing. However, many kinds of noise are generated in the transmission and reception process and affect the information of the signal. For this reason, the noise removal is essential as a preprocessing process. In this paper, we propose an algorithm to remove mixed noise of impulse noise and AWGN. The proposed algorithm restores the image through noise determination and pixel change for efficient noise removal. Unlike the conventional method, noise is removed by minimizing both noise effects. Simulation showed excellent noise removal characteristic results were compared and analyzed using the PSNR for such decisions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.394-400
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• 2016

Currently, with the rapid development of the digital age, multimedia-related image devices become popular. However image deterioration is generated by multiple causes during the transmission process, with typical example of salt and pepper noise. When the noise of high density is added, existing methods are deteriorated in the characteristics of removal noise. After judging the noise condition to remove the salt and pepper noise, if the center pixel is the non-noise pixel, it is replaced with the original pixel. On the other hand, if it is the noise pixel, algorithm is suggested by the study, where the histogram of the corrupted image and the median filters are used. And for objective judgment, the proposed algorithm was compared with existing methods and PSNR(peak signal to noise ratio) was used as judgment standard. As the result of the simulation, The proposed algorithm shows a high PSNR of 32.57[dB] for Lena images that had been damaged of a high density salt and pepper noise(P=60%), Compared to the existing CWMF, A-TMF and AWMF there were improvements by 21.67[dB], 18.07[dB], and 20.13[dB], respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.989-995
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• 2022

Currently, the demand for image processing is increasing due to the development of IT technology, and active research is being conducted. Since image data generates image noise due to various external causes, and thus degrades the performance of the image, noise removal is essential. Salt and Pepper noise is a representative image noise, and various studies are being conducted to remove it. Existing algorithms include A-TMF, AFMF, LIWF, but these have the disadvantage that their performance is somewhat insufficient. Therefore, in this paper, we propose an algorithm that performs filtering using linear interpolation with effective pixels existing around the central pixel only in case of noise after performing noise judgment in order to efficiently remove salt and pepper noise. In order to judge the performance of the proposed algorithm, it was compared using the processed image of the previously studied algorithm and PSNR.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.441-443
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• 2022

Currently, image processing is being used in various fields such as image analysis, image recognition, and factory automation according to the development of IT technology. Salt and pepper noise is generated due to various external factors in the process of acquiring or transmitting an image, which deteriorates the image quality. Therefore, noise removal to improve image quality is essential. Various methods have been proposed to remove salt and pepper noise, and representative examples include AF, MF, and A-TMF. However, the conventional filter has insufficient noise removal performance in a high-density noise environment. Therefore, in this paper, we propose an algorithm for estimating and processing the original pixel by using the modified distance weight filter only in the case of noise, and replacing the original pixel in case of non-noise after performing noise judgment. To evaluate the performance of the proposed algorithm, we compare and analyze it with existing algorithms using PSNR.

• 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.