• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1177-1182
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• 2011

The image signals are corrupted by various noises in signal processing and the noises caused the degradation phenomenon. gaussian noise occurs in the process of transmission. Many studies are being accomplished to restore those signals which corrupted by additive gaussian noise. In this paper, the algorithm is proposed to remove AWGN. The algorithm first calculates the mask's standard deviation and next according to the thresholds separated as three levels, then calculates the weight which for different location in the mask's pixels. At last the mean value of the modified mean filter's is the output. Also we compare existing methods through the simulation and using PSNR as the standard of judgement of improvement effect.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.10
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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.