Multidimensional Directional Filter Banks and Surfacelets


Y. M. Lu and M. N. Do, “Multidimensional Directional Filter Banks and Surfacelets,” IEEE Transactions on Image Processing, vol. 16, no. 4, pp. 918-931, 2007.
ndfb_surf.pdf1.58 MB


In 1992, Bamberger and Smith proposed the directional filter bank (DFB) for an efficient directional decomposition of 2-D signals. Due to the nonseparable nature of the system, extending the DFB to higher dimensions while still retaining its attractive features is a challenging and previously unsolved problem. We propose a new family of filter banks, named NDFB, that can achieve the directional decomposition of arbitrary  N-dimensional (N >= 2) signals with a simple and efficient tree-structured construction. In 3-D, the ideal passbands of the proposed NDFB are rectangular-based pyramids radiating out from the origin at different orientations and tiling the entire frequency space. The proposed NDFB achieves perfect reconstruction via an iterated filter bank with a redundancy factor of in N-D. The angular resolution of the proposed NDFB can be iteratively refined by invoking more levels of decomposition through a simple expansion rule. By combining the NDFB with a new multiscale pyramid, we propose the surfacelet transform, which can be used to efficiently capture and represent surface-like singularities in multidimensional data.

MATLAB and C++ code

Last updated on 11/12/2013