Multiscale Keypoint Detection using the Dual-Tree Complex Wavelet Transform

We present a novel approach to detecting multiscale keypoints using the dual tree complex wavelet transform (DTCWT). We show that it is a well-suited basis for this problem as it is directionally selective, smoothly shift invariant, optimally decimated at coarse scales and invertible (no loss of information). Our detection scheme is fast because of the decimated nature of the DTCWT and yet provides accurate and robust keypoint localisation, thanks to the use of the "accumulated energy map". The regularity of this map is used to introduce a new mechanism for robust keypoint scale selection. Key-points of different nature and size can be detected with limited redundancy, in a way which is consistent with our visual perception. Furthermore results show better robustness against rotation compared to the SIFT detector.