• Title/Summary/Keyword: Salt & pepper 잡음

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Noise Removal of Image Signals using Inflection Points on Histogram (히스토그램의 변곡점을 이용한 영상 신호의 잡음 제거)

  • Baek, Ji-Hyeon;Kim, Nam-Ho
    • 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.

A Study on Edge Detection Algorithm using Modified Mask in Salt and Pepper Noise Images (Salt and Pepper 잡음 영상에서 변형된 마스크를 이용한 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.1
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    • pp.210-216
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    • 2014
  • The edge in the image is a part which the brightness changes rapidly between the object and the object or objects and background, and includes information of the features such as size, position, orientation, and texture of the object. The edge detection is the technique that acquires these information of the images, and now the researches to detect edges are making steady progress. Typical conventional edge detection methods are Sobel, Prewitt, Roberts using the first derivative operator and Laplacian method using the second derivative operator and so on. These methods is more or less insufficient that the characteristics of the edge detection in the image added salt and pepper noise. therefore, in this paper, an edge detection algorithm using modified mask that applies different size mask according to noise density of local mask is proposed.

High Density Salt & Pepper Noise Reduction using Lagrange Interpolation and Iteration Process (Lagrange 보간 및 반복 처리를 이용한 고밀도 Salt & Pepper 잡음 제거)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.4
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    • pp.965-972
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    • 2015
  • Along with the rapid development in digital times, image media are being used in internet, computer and digital camera. But image deterioration occurs due to various exterior reasons in the procedures of acquisition, processing, transmission and recording of digital image and major reason is noise. Therefore in order to remove salt & pepper noise, this study suggested the algorithm which replaces the noise to original pixel in case of non-noise, and processes the noise with Lagrange interpolation method in case of noise. In case high density noise was added and the noise could not be removed, noise characteristics were improved by processing the noises repeatedly. And for objective judgment, this method was compared with existing methods and PSNR(peak signal to noise ratio) was used as judgment standard.

A Study on Mixed Noise Removal using Pixel Direction Factors and Weighted Value Mask (화소의 방향요소 및 가중치 마스크를 이용한 복합잡음 제거에 관한 연구)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • 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.

A Study on Weighting Filter Considering Directivity in High Density Salt and Pepper Noise (고밀도 Salt and Pepper 잡음 환경에서 방향성을 고려한 가중치 필터에 관한 연구)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.925-928
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    • 2015
  • The application fields of the image processing get gradually diversified as the society develops to the highly leveled digital information era and is highlighted as an important field. Especially, many studies on image restoration, a key technology in the image processing have been carried out. This paper proposed a filter which applies the directivity and spatial weighting based on the degraded pixels in order to restore the image degraded in the high density salt and pepper noise environment. In addition, this paper compared this filter with the current methods for objective judgment using PSNR(peak signal to noise ratio) as a criterion of judgment.

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A Study on Mixed Noise Removal using Standard Deviation and Noise Density (표준편차 및 잡음 밀도를 이용한 복합잡음 제거 알고리즘에 관한 연구)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.173-175
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    • 2017
  • With the rapid progress of the digital area has come the increase in demand for multi-media services. Imaging processing as a result is being hailed as a technological field that can offer smart and efficient methods for the processing and analysis of images. In general, noise exist in various types, depending on the cause and form. Some leading examples of noise are AWGN(additive white Gaussian noise), salt and pepper noise and complex noise. This study suggests an algorithm to remove complex noise by using the standard deviation and noise density of the partial mask in order to effectively remove complex noise in images.

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Noise Reduction Algorithm of Salt-and-Pepper Using Reliability-based Weighted Mean Filter (복원화소의 신뢰도 기반 가중 평균 필터를 활용한 Salt-and-Pepper 잡음 제거 알고리즘)

  • Kim, Donghyung
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.17 no.2
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    • pp.1-11
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    • 2021
  • Salt and pepper is a type of impulse noise. It may appear due to an error in the image transmission process and image storage memory. This noise changes the pixel value at any position in the image to 0 (in case of pepper noise) or 255 (in case of salt noise). In this paper, we present an algorithm for SAP noise reduction. The proposed method consists of three steps. In the first step, the location of the SAP noise is detected, and in the second step, the pixel value of the detected location is restored using a weighted average of the surrounding pixel values. In the last step, a reliability matrix around the reconstructed pixels is constructed, and additional correction is performed with a weighted average using this. As a result of the experiment, the proposed method appears to have similar or higher objective and subjective image quality than previous methods for almost all SAP noise ratios.

Post Processing Noise Reduction Algorithm of SAP Using Convolution Neural Network (합성곱신경망을 이용한 SAP 잡음 제거 후처리 알고리즘)

  • Kim Donghyung
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.19 no.2
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    • pp.57-68
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    • 2023
  • Because salt and pepper noise is a type of impulse, even a small amount of noise could cause a large image degradation. In this paper, we proposed a salt-and-pepper noise removal method using the convolutional neural network. It consists of four phases. In the first step, the proposed method reconstructs noisy image using a traditional salt-and-pepper noise reduction method, and in the second step, the result image of previous step is filtered with Gaussian low pass filter. After that, we reconstruct the filtered image using convolution neural network. In the last step, the pixels with salt-and-pepper noise are replaced with the result of previous phase. Simulation results show that the proposed method yields not only objective image qualities(PSNR, SSIM) but also subjective image qualities for all SAP noise ratios.

Noise Reduction of Binary Image in Non-Impulse Noise (비임펄스 잡음이 포함된 이진영상의 잡음제거)

  • 김재석;정성옥;오무송
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.511-513
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    • 2002
  • 본 논문에서는 영상에 Salt-Pepper와 같은 임펄스 잡음이 존재하는 영상에 대한 잡음 제거는 기존의 잡음제거 방법인 미디언 필터를 이용하여 잡음을 제거할 수 있지만 임펄스 잡음이 아닌 비임펄스 잡음이 포함된 영상에 대해서는 미디언 필터를 이용하여 비임펄스 잡음이 제거되지 않으므로 임펄스 잡음이 아닌 비임펄스 잡음이 존재하는 영상에 대한 잡음 제거를 형태학적 연산을 이용하여 잡음 제거하는 방법을 제안한다.

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Wireless Communication Quality Improvement Through DSES Alarmed Noise Image Restoration

  • Ki-Hwan, Kim;HyunHo, Kim;HoonJae, Lee
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.2
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    • pp.55-62
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    • 2023
  • Radio waves must pass through the unstable atmosphere for successful wireless data transmission from space to ground stations. Data link algorithms required by the International Space Data Systems Advisory Committee (CCSDS) must be capable of detecting and resynchronizing cryptographic and receiver-side errors. However, error recovery is not part of the CCSDS requirements. This paper proposes an algorithm that enables robustness and error recovery against various noises. We experimented with environments such as Gaussian, Salt, Pepper, and S&P noise through noise reduction filters, filters that improve sharpness, and EDSR. In addition, we compare similar algorithms SES Alarmed and DSES Alarmed.