• 한국정보통신학회논문지
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• 제15권5호
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• pp.1177-1182
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• 2011

영상신호를 처리하는 과정에서 다양한 잡음에 의해 영상의 열화가 발생하고 있으며, 가우시안 잡음은 전송 등의 과정에서 영상에 의존적으로 발생한다. 이러한 가우시안 잡음을 제거하기 위한 다양한 연구가 이루어지고 있다. 본 논문에서는 AWGN을 제거하기 위하여 마스크 내의 표준편차를 구하고 그 값을 임계값과 비교하여 레벨을 나누어 마스크 내의 각 화소값에 주는 가중치를 구한 후, 평균치를 출력영상의 화소값으로 하는 변형된 weighted mean filter를 제안하였다. 그리고 시뮬레이션을 통해 기존의 방법들과 그 성능을 비교하였고 판단기준으로 PSNR을 사용하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권10호
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• pp.468-476
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• 2002

Digital images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in medical radio-fluoroscopy images is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in diagnosis. We proposed adaptive weighed median(AWM) filters based on local statistics. We showed two ways of realizing the AWM filters. One is a simple type of AWM filter, which is constructed by Homogeneous factor(HF). Homogeneous factor(HF) from the noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the diagnostic systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by Visual C++ language on a IBM-PC Pentium 550 for testing purposes and the effects and results of the filter in the various levels of noise and images were proposed by comparing the values of NMSE(normalized mean square error) with the value of the other existing filtering methods.