This paper introduces the phase congruency model with illumination and contrast invariance for image matching, and extends the model to feature orientation in phase congruency. Based on the orientated gradient histogram concept, a local feature descriptor named "local histogram of orientated phase congruency (LHOPC)" is developed using the intensity and orientation of phase congruency. The Euclidean distance between LHOPC descriptors is used as similarity metric to achieve correspondences. The proposed method is evaluated with four pairs of multi-source remote sensing images. The experimental results show that LHOPC is more robust to the radiation differences between images, and performs better than the SIFT and SURF algorithms.