• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2717-2723
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• 2015

Recently, digital image processing is being applied in various areas of broadcasting, communication, computer graphic and medical science. But, degradation of images occurs in the process of digital image acquisition, processing and transmission. Therefore, in order to remove the mixed noise, this paper suggested the image restoration algorithm to process salt and pepper noise with weighted filters according to 4 direction pixel changes after judging the noise and to process AWGN with weighted filters which have individually different characteristics. Regarding the processed results by applying Boat images which were corrupted by salt and pepper noise(P=40%), suggested algorithm showed the improvement by 1.33[dB], 1.41[dB], 0.51[dB] respectively compared with the existing CWMF, AWMF, MMF.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.798-801
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• 2014

Nowadays, the demand for multimedia services has grown with the rapid evolution in the digital era. But due to external causes in the process of processing, transmitting and storing image data, the images are damaged. One of the major causes of such damage is known to be noise. Some of the most commonly used methods for removing noise are CWMF(center weighted median filter), A-TMF(alpha-trimmed mean filter) and AWMF(adaptive weighted median filter). However, these filters all leave a bit to be desired in removing noise in a complex noise environment. Therefore this paper suggest an image restoration filter algorithm that first judges the noise and sets a adjustment weight based on the median value and distance of the mask to remove the complex noise. For an objective analysis, the results were compared against existing methods and the PSNR(peak signal to noise ratio) was used as a reference.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1076-1081
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• 2019

In response to the recent development of IT technologies, there are more demands for visual devices such as display. However, noise is generated in the process of sending video data due to various reasons. Noise is the representative noise which is commonly found. While A-TMF, CWMF, and AMF are the typical ways for removing Salt and Pepper noise, the noise is not removed well in high-density noise environment. To remove the noise in the high-density noise environment, this study suggested an algorithm which identifies whether it's noise or not. If it's not a noise, matches the original pixel. If it's a noise, divide the $3{\times}3$ local mask into the area of the element treated and the area of the element to be processed. Then, algorithm proposes to apply different weights for each element to treat it as an average filter. To analyze the performance of the algorithm, this study compared PSNR to compare the algorithm with other existing methods.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.3
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• pp.113-120
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• 2020

With the recent development of communication equipment, the demand for communication equipment is gradually increasing. Accordingly, various signal processing has been studied. In the case of an image, noise removal is an indispensable step because noise propagation problems may occur if noise is not removed in the pre-processing process. Salt and Pepper noise is a typical impulse noise with two extremes. Various studies have been conducted to remove such noise, and there are CWMF, MF and MMF. However, the existing methods are somewhat insufficient in the high-density noise region. Therefore, in this study, we have proposed an algorithm that filters the size of the mask according to the number of noises inside the 7×7 mask and filters it with a modified switching filter using the histogram distribution of the image. In the case of the proposed algorithm, noise can be effectively removed in a high-density noise region. For objective judgment, PSNR was used to compare and analyze with existing algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1431-1436
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• 2020

In modern society, various video devices such as CCTV and black boxes are used for convenience. However, noise is frequently generated in the process of transmitting and receiving video images and video signals photographed at night. If such noise is not eliminated, the problem that the image is difficult to identify is generated. Accordingly, noise elimination of images in the image information is an indispensable step. Salt and Pepper noises are typical impulse noises among image noises. Previous research has been carried out as a method for eliminating noise, and CWMF, MMF and A-TMF are typical methods. In common, such a filter exhibits excellent performance in a low-density noise area, but a disadvantage is that noise elimination performance in a high-density noise area is somewhat insufficient. Accordingly, the proposed algorithm uses the inflection point of the histogram graph to separate areas and remove singular points, and proposes a weighting filter utilizing histogram distribution. PSNR was used for objective judgment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.474-480
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• 2020

With the advent of the Fourth Industrial Revolution, many new technologies are being utilized. In particular, video signals are used in various fields. However, when transmitting and receiving video signals, salt and pepper noise and additive white Gaussian noise (AWGN) occur for multiple reasons. Failure to remove such noise when performing image processing can cause problems. Generally, filters such as CWMF, MF, and AMF remove noise. However, these filters perform somewhat poorly in the high-density noise domain and cause smoothing, resulting in slightly lower retention of the edge components. In this paper, we propose an algorithm by effectively eliminating salt and pepper noise using a modified weight filter using standard deviation. In order to prove the noise reduction performance of the proposed algorithm, we compared it with the existing algorithm using PSNR and magnified images.

• The Journal of the Korea Contents Association
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• v.4 no.4
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• pp.205-213
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• 2004

In this paper, we proposed a wavelet phase-only filter modulation synthetic discriminant function joint transform correlator(WPOfSDF-JTC) for scale invariant pattern recognition, and an improved algorithm to reduce the filter synthesis time. Computer simulation showed that the proposed filter has better SNR than CWMF if input image has random noise and the improved synthesis algorithm can reduce the iteration time. We used frequency selective JTC to solve the problem of the optical alignment and eliminate the autocorrelation and crosscorrelation between each input image.