The Transactions of the Korean Institute of Electrical Engineers D (대한전기학회논문지:시스템및제어부문D)

The Korean Institute of Electrical Engineers (대한전기학회)
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Impulse Noise Detection Using Self-Organizing Neural Network and Its Application to Selective Median Filtering

Self-Organizing Neural Network를 이용한 임펄스 노이즈 검출과 선택적 미디언 필터 적용

  • 이종호 (인하대 공대 정보통신공학부) ;
  • 동성수 (용인송담대 디지털전자정보과) ;
  • 위재우 (인하대 공대 전기공학과) ;
  • 송승민 (인하대 공대 정보통신공학과)
  • Published : 2005.03.01
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Abstract

Preserving image features, edges and details in the process of impulsive noise filtering is an important problem. To avoid image blurring, only corrupted pixels must be filtered. In this paper, we propose an effective impulse noise detection method using Self-Organizing Neural Network(SONN) which applies median filter selectively for removing random-valued impulse noises while preserving image features, edges and details. Using a $3\times3$ window, we obtain useful local features with which impulse noise patterns are classified. SONN is trained with sample image patterns and each pixel pattern is classified by its local information in the image. The results of the experiments with various images which are the noise range of $5-15\%$ show that our method performs better than other methods which use multiple threshold values for impulse noise detection.

Keywords

References

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