A Mixed Noise Removal Method Based on Total Variation

N.H. Thanh Dang, Sergey D. Dvoenko, Viet Sang Dinh


Due to the technology limits, digital images always include some defects, such as noise. Noise reduces image quality and affects the result of imageprocessing. While in most cases, noise has Gaussian distribution, in biomedical images, noise is usually a combination of Poisson and Gaussian noises. This combination is naturally considered as a superposition of Gaussian noise over Poisson noise. In this paper, we propose a method to remove such a type of mixed noise based on anovel approach: we consider the superposition of noises like a linear combination. We use the idea of the total variation of an image intensity (brightness) function to remove this combination of noises.

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