A multiresolution edge detection algorithm for speckle images is propo
sed. Due to the signal dependence of speckle noise, the variance of a
speckle image depends on the local average intensity; thus an edge det
ection method independent of the local average intensity is desirable
for correct extraction of real, significant changes in an original sig
nal, In the proposed method, each area having different resolution is
first classified according to the statistical properties of a speckle
image, namely, a discontinuity measure such as the ratio of variance t
o mean square or the maximum difference between the real and theoretic
al cumulative density functions. Then the real edges are extracted in
a multiresolution environment. Computer simulation with several test i
mages shows that the proposed method significantly reduces false edges
in relatively homogeneous areas while detecting fine details properly
. Also, simulation results from the conventional edge detection method
s for speckle images are compared with those of the proposed method.