Abstract
We propose a novel technique for ultrasound speckle reduction based on iterative solutions to the coherent diffusion equation with the speckled image considered as the initial heat distribution. According to the extent of speckle, the model changes progressively from isotropic diffusion through anisotropic coherent diffusion to mean curvature motion. This structure maximally low-pass filters those parts of the image corresponding to fully-formed speckle, while preserving information associated with resolved object structures. The distance measure used to assess the deviation between images is embedded within the diffusivity tensor and is utilized as an intrinsic stopping criterion that ends the diffusion process completely in all directions when the deviation between the original and the filtered image exceeds the speckle limit. This model is termed pseudo-biased diffusion due to this unique formulation. Hence, there is no need for specifying the number of iterations in advance as with previous methods. Moreover, the steady, state solution does not converge to the trivial single gray level solution, but rather to an image that is close in structure to the original but with speckle noise substantially reduced. Efficient discretization schemes allow large time steps to be used in obtaining the solution to achieve real-time processing.