  Edge Detection Methods Based on Differential Phase Congruency of Monogenic
Image Abstract: Edge detection has been widely used in medical image processing
and automatic diagnosis. Some novel edge detection algorithms,based on the
monogenic scale-space, are proposed by detecting points of local extrema in
local amplitude, the local attenuation and modified differential phase
congruency methods. The monogenic scale-space is obtained from a known image by
Poisson and conjugate Poisson filtering. In mathematics, it is the Hardy space
in the upper half-space. The boundary value of the monogenic scale-space
representation is a monogenic image. In the monogenic scale-space, the
definitions involving scale, such as local amplitude,local attenuation, local
phase angle, local phase vector and local frequency (phase derivatives) are
proposed. Using Clifford analysis, the relations between the local attenuation
and the local phase vector are obtained. These study will be improved the
understanding of image analysis in higher dimensional spaces. Experimental
results are shown by using some typical images.
