A telegraph-diffusion model coupled to an edge-variable reaction-diffusion equation is proven to have a unique weak solution, and it modestly improves despeckling metrics over two comparison models on three test images.
A Gray Level Indicator-Based Regularized Telegraph Diffusion Equation Applied to Image Despeckling
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abstract
In this work, a gray level indicator based non-linear telegraph diffusion model is presented for multiplicative noise removal problem. Most of the researchers focus only on diffusion equation-based model for multiplicative noise removal problem. The suggested model uses the benefit of the combined effect of diffusion equation as well as the wave equation. Wave nature of the model preserves the high oscillatory and texture pattern in an image. In this model, the diffusion coefficient depends not only on the image gradient but also on the gray level of the image, which controls the diffusion process better than only gradient-based diffusion models. Moreover, we prove the well-posedness of the present model using Schauder fixed point theorem. Furthermore, we show the superiority of the proposed model over a recently developed method on a set of gray level test images which are corrupted by speckle noise.
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math.AP 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
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Well-posedness study of a non-linear hyperbolic-parabolic coupled system applied to image speckle reduction
A telegraph-diffusion model coupled to an edge-variable reaction-diffusion equation is proven to have a unique weak solution, and it modestly improves despeckling metrics over two comparison models on three test images.