A novel algorithm is proposed based on 2-D discrete Hilbert transform.It has been verified that Hilbert transform can be used to detect the edge features from images.The magnitude of signal is not changed,and the phase is shifted in frequency domain after transforming by Hilbert transform.Namely,when the signal is negative,the phaseshift is +90°;when it is positive,the phaseshifit is-90°.There are peaks and valleys on features of signal after Hilbert transform.Thus,the 2-D discrete Hilbert transform to detect image edges is proposed.Because of the directionality of the 2-D discrete Hilbert transform in edge detection,the quadratic sum of two orthogonal 2-D discrete Hilbert transform is calculated to complete the edge detection.Furthermore,Gaussian function is introduced into the 2-D discrete Hilbert transform to reduce the influence from noises,and PSNR(peak signal to noise ratio) is used to determine the optimal parameter σ.An evaluation between the proposed algorithm and the others is realized to verify the result of edge detection.Remotely sensed imageries are chosen as test data in edge features detection.The results of detection show that the proposed algorithm is effective in edge features detection.