Phase Congruency was introduced as a new method to detect features from high-resolution remotely sensed imagery.Three objects i.e.paddy

road

and factory

were selected from the IKONOS Pan imagery of Nanjing.The Phase Congruency feature images were obtained by applying Phase Congruency model to the images with two-octave Log Gabor wavelets filters over 5 scales and 6 orientations.For qualitative comparison

the outputs of the Sobel and Canny detector were also presented.The results show that Phase Congruency response value was invariant in image local illumination and contrast.The other obvious difference was that the Sobel and Canny detector produced responses on each side of linear features

whereas the Phase Congruency produced a response centered on the line.The effects of varying filter orientation or scale and the effect of adding noise in the feature detection between Phase Congruency and Canny method then were compared.It was found that Phase Congruency could obtain more accurate localization because it does not need low-pass filter to restrain noise first.It was also shown that noise had been successfully ignored in the smooth regions of the image

unlike the Canny detector results fluctuated all over the image.With this invariant image feature detector

better image segmentation and object-oriented image recognition are possible.