• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.691-693
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• 2017

As the modern society develops into the digital information age, the application field is gradually expanded and used as an important field. The image data is deteriorated due to various causes in the process of transmitting the image, and typically there is salt & pepper noise. Conventional methods for removing salt & pepper noise are somewhat lacking in noise canceling characteristics. In this paper, we propose a weighted filter using the histogram of the image damaged by salt & pepper noise and a spline interpolation method according to the direction of the local mask.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.230-236
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• 2015

In these digital times, the image signal processing is being used in various areas like vehicle recognition, security, and robotics. Generally, the image deterioration occurs by salt & pepper noise in the procedures of image transmission, storage, and processing. Methods to remove this noise are SMF, CWMF, and SWMF and these methods have few unsatisfactory noise reduction characteristics in salt & pepper noise environment. Therefore, in order to mitigate salt & pepper noise which is added in the image, this study suggested an algorithm which subdivides the masks in the image into four areas and processes using non-noise pixel numbers in each area. Additionally, in order to prove the excellence of the proposed algorithm, relevant performances were compared with existing methods using PSNR.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.903-905
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• 2015

The need for digital devices is increasing in the digital age. In general, noise in images occurs during the process of compression, recognition and processing due to many reasons. Some of the filters used to remove salt and pepper noise include SMF, CWMF and AMF. In areas where the noise density is high, the removal of noise is undermined. This paper suggests an adjusted median filter algorithm that preserves the non-noise pixels while transforming the noise pixels to more effectively remove salt and pepper noise.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.346-349
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• 2017

Digital image processing is widely used in a variety of areas, and noise elimination is used as the preprocessing in all the image processing processes. Degradation is occurred in the image data due to multiple reasons. Degradation is to add the noise in the image signal, and salt and pepper noise is the representative one to cause degradation. Therefore, image restoration algorithm was proposed to process with histogram weight filter and median filter by the noise density of local mask to restore the damaged image in the salt and pepper noise environment, in this article. In addition, it was compared with the existing methods using peak signal to noise ratio(PSNR) as the objective determination factor of improvement effect.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.312-314
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• 2015

With progress in information technology, demand for imaging devices such as display devices is increasing. But noise occurs due to various reasons during the process of acquiring, transmitting or processing the image data. Filters used to remove salt and pepper noise include SMF, CWMF and AWMF. In areas where the noise density is high, the removal of noise is undermined. This paper suggests an adjusted median filter algorithm that transforms the noise pixels to more effectively remove salt and pepper noise.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1383-1388
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• 2016

Although image signal processing is used in many fields, degradation takes place in the process of transmitting image data by several causes. CWMF, A-TMF, and AWMF are the typical methods to eliminate noises from image data damaged under salt and pepper noise environment. However, those filters are not effective for noise rejection under highly dense noise environment. In this respect, the present study proposed an algorithm to remove in salt and pepper noise. In case the center pixel is determined to be non-noise, it is replaced with original pixel. In case the center pixel is noise, it segments local mask into 4 directions and uses linear interpolation to estimate original pixel. And then it applies spatial weight to the estimated pixel. The proposed algorithm shows a high PSNR of 24.56[dB] for House images that had been damaged of salt and pepper noise(P = 50%), compared to the existing CWMF, A-TMF and AWMF there were improvements by 16.46[dB], 12.28[dB], and 12.32[dB], respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.343-345
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• 2017

In digital era image processing has been utilized in a variety of media such as TV, camera and smart phone. However, in the process of analyzing, recognizing, and processing image data, deterioration occurs due to various causes and Salt & Pepper noise occurs. Typical methods for removing such noise include SMF, CWMF, and SWMF. However, existing methods have a somewhat poor noise canceling characteristic in Salt & Pepper noise environment. Therefore, in this paper, we propose an algorithm to remove Salt & Pepper noise effectively by using bilinear interpolation method and median filter according to noise density of local mask. And using the PSNR(Peak Signal to Noise Ratio) it compared to the existing methods and their performance in order to determine the performance of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.397-400
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• 2016

In digital images, the addition due to noise occurs in the process of obtaining, saving, and transmitting. For examples of noise, there are salt and pepper noise, Gaussian noise, and composition noise where various noises are mixed. Existing filters have insufficient noise removal characteristics because it uses single filters in composite noise environment. Therefore the study suggested a switching filter that processes with special weighted value and median filter according to local mask salt and pepper noise density when central pixel is damaged by salt and pepper noise, and processes by applying weighted values differently according to standard deviation of local mask when damaged by Gaussian noise.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.953-955
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• 2016

Degradation is occurred in the process of the signal transmission in the image processing system due to various reasons. Degradation is noise addition in the image signal and the representative one to cause degradation is salt and pepper noise. Therefore, image restoring filter was suggested in this article to apply and process weighted value by the changes of each directional pixel upon breakdown of local mask with 8 directions in order to restore the damaged image in the environment of salt and pepper noise. In addition, peak signal to noise ratio (PSNR) was used to compare the existing method as the objective determinant standard of the improvement effect.

• 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.