Description: Abstract: An image de-noising model by integrating anisotropic diffusion with USFFT Curvelet transform was proposed,
which combined the strongpoint of Curvelet transform with anisotropic diffusion (P-M diffusion). By choosing appropriate
gradient threshold K through p-norms and carrying out the P-M diffusion process depend on the different scale matrixes
of Curvelet coefficient of the image from Curvelet transform iterations, as a result, the improved model made it
possible to carry out the new P-M diffusion de-noising process based on multi-scale analysis of the image. The experiment
results have demonstrated that the model can avert the stair-casing effect in the traditional P-M diffusion effectively
and keep the textures and details of images better.
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