Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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A Study on Salt & Pepper Noise Removal using the Pixel Distribution of Local Mask

국부 마스크의 화소 분포를 이용한 Salt & Pepper 잡음 제거에 관한 연구

  • Kwon, Se-Ik (Dept. of Control and Instrumentation Eng., Pukyong National University) ;
  • Kim, Nam-Ho (Dept. of Control and Instrumentation Eng., Pukyong National University)
  • Received : 2015.05.22
  • Accepted : 2015.07.01
  • Published : 2015.08.20
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Abstract

Due to the recent progress in information technology, demand for video imaging devices such as displays has grown. In general, images experience deterioration during the process of transmission due to various reasons. Many studies have boon undertaken on ways o reduce such noise. This paper6 suggests an algorithm that makes a judgment on the noise in order to remove the salt & pepper noise and replaces original pixels if they are non-noise while processing noise according to its density. The suggested algorithm shows a high PSNR of 30.49[dB] for Goldhill images that had been damaged of a high density salt & pepper noise(P = 60%), Compared to the exising CWMF, SWMF, and A-TMF, there were improvements by 17.74[dB], 11.52[dB], and 13.76[dB], respectively.

최근 IT 기술의 발전에 따라 디스플레이 등 영상장치들에 대한 요구가 갈수록 높아지고 있다. 일반적으로 영상은 전송과정에서 여러 원인으로 열화가 발생하며 이러한 잡음을 제거하기 위해 활발한 연구가 진행되고 있다. 따라서 본 논문에서는 salt & pepper 잡음을 제거하기 위해 잡음 판단 후, 비잡음인 경우 원 화소로 대치하고, 잡음인 경우 잡음 밀도에 따라 처리하는 알고리즘을 제안하였다. 제안한 알고리즘은 salt & pepper 잡음(P = 60%)의 고밀도 잡음에 훼손된 Goldhill 영상은 30.49[dB]의 높은 PSNR을 보이고 있고, 기존의 CWMF, SWMF, A-TMF에 비해 각각 17.74[dB], 11.52[dB], 13.76[dB] 개선되었다.

Keywords

References

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  2. RW. Luo, "Efficient removal of impulse noise from digital images," IEEE Trans. Consumer Electron, vol. 52, no. 2, pp.523-527, May 2006. https://doi.org/10.1109/TCE.2006.1649674
  3. Se-Ik Kwon and Nam-Ho Kim, "A Study on Modified Spatial Weighted Filter in Mixed Noise Environments," JICCE, vol. 19, no. 1, 2015.
  4. Öten, Remzi and De Figueiredo, Rlui J P, "Adaptive Alpha-Trimmed Mean Filters Under Deviations From Assumed Noise Model", IEEE Trans, Image Processing, vol. 13, no. 5, pp. 627-639, May 2004. https://doi.org/10.1109/TIP.2003.821115
  5. Xu Long and Nam-Ho Kim, "An Improved Weighted Filter for AWGN Removal", JKIICE, vol. 17, no. 5, pp. 1227-1232, 2013.
  6. Sang-Woou Hong and Nam-Ho Kim, "A Study on Median Filter using Directional Mask in Salt & Pepper Noise Environments", JKIICE, vol. 19, no. 1, pp. 203-236, 2015.

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