Image Denoising: A DAMRF Model

The problem of reconstructing digital images from degraded measurement is regarded as a problem of importance in various fields of engineering and imaging science. The main goal of denoising is to restore an image from its noisy version to obtain a visually high quality image. In this paper we propose a novel method that uses Markov random field (MRF) for image denoising.

First, the image is modeled as MRF and then the maximum a posteriori (MAP) estimation method is used to derive the cost function. Afterwards it is optimized to obtain denoised image. The result is compared with traditional spatial domain methods. The visual and quantitative evaluation suggests that the proposed method yields better results.

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