• Title/Summary/Keyword: Reliability-based Weighted Mean Filter

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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.

Adaptive Switching Filtering Algorithm for SAP noise (SAP 잡음 제거를 위한 적응적 스위칭 필터링 알고리즘)

  • Kim, Donghyung
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.18 no.1
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    • pp.25-35
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    • 2022
  • The SAP(salt-and-pepper) noise changes the pixel value to the maximum and minimum values of the dynamic region of the pixel. For this reason, unlike white Gaussian noise, SAP noise can predict the ratio of noise relatively easily. Because the condition of the neighboring pixels that can be referenced changes according to the noise ratio, it is necessary to apply different noise reduction methods according to the noise ratio. This paper proposes an adaptive switching filtering algorithm which can eliminates the SAP noise. It consists of two phases. It first detects the location of the SAP noise and calculates the noise ratio. After that, the image is reconstructed using different methods depending on which of the three sections the calculated noise ratio belongs to. As a result of the experiment, the proposed method showed superior objective and subjective image quality compared to the previous methods such as MF, AFSWMF, NAMF and RWMF.