earticle

영어

This paper focuses on investigating robust edge detection methods using wavelet transform (WT) techniques. Based on the properties that the WT coefficients due to the edges concentrate and are highly correlated in the region of support (RoS) of the wavelet filters while those due to the white Gaussian noise are still Gaussian, this paper presents two robust WT-based correlation edge detectors by using the correlation of WT coefficients in the RoS of wavelet filters. The first one generates its decision statistics by integrating the point-wise energy of the WT coefficients in the RoS of wavelet filters, which is called as WT-based energy edge detector. The second one generates its decision statistics by integrating the correlation of the WT coefficients in the RoS of wavelet filters, which is called as WT-based coherent edge detector. Moreover, the statistical properties as well as the optimal integration length of these two edge detectors are derived. Finally, simulations are carried out to illustrate the detection performance of the proposed WT-based correlation edge detectors and compare them with the existing edge detection methods.