Edge detection based on wavelet domain spatial correlation thresholding

This paper proposes a scale correlation-based edge detection scheme. A scale correlation function is defined as the product of detection filter's response at two scales. With the proper choice of detection filters such as the first derivative of Gaussian, the scale correlation will magnify the edge structures and suppress the noise. Unlike many of the multiscale techniques that first form the edge maps at several scales and then synthesize them together, in our scheme, edges are determined as the local maxima directly in the correlation function. The detection and localization criteria of the scale correlation are defined. It is shown that with little loss in detection criterion, much improvement is gained on localization criterion. Using scale correlation,the dislocation of neighboring edges is also improved when the width of detection filter is set large to smooth noise.