α scale spaces filters for phase based edge detection in ultrasound images

An inherent characteristic of coherent imaging, including ultrasound imaging, is the presence of speckle noise with strong inhomogeneities. It makes modelling difficult and therefore it complicates their processing. However, it has been previously shown that these images respond well to local phase-based methods. Furthermore, the recent re-emergence of the α scale spaces theory opens new possibilities of phase-based image processing. In this paper, we make use of this new unified representation to derive new families of bandpass quadrature filters. This construction leads to a generalised α kernel filters including the commonly known families derived from the Gaussian and the Poisson kernels. The properties of each family are first presented and then, experiments on realistic simulations of ultrasound images are shown to demonstrate how the suggested filters can be used for edge detection.