Nonsubsampled contourilet transform: filter design and applications in denoising

In this paper we study the nonsubsampled contourlet transform. We address the corresponding filter design problem using the Mc-Clellan transformation. We show how zeroes can be imposed in the filters so that the iterated structure produces regular basis functions. The proposed design framework yields filters that can be implemented efficiently through a lifting factorization. We apply the constructed transform in image noise removal where the results obtained are comparable to the state-of-the art, being superior in some cases.