Directionally selective fractional wavelet transform using a 2-d non-separable unbalanced lifting structure
Çetin, A. Enis
Computational Intelligence for Multimedia Understanding
Springer, Berlin, Heidelberg
102 - 113
Item Usage Stats
MetadataShow full item record
In this paper, we extend the recently introduced concept of fractional wavelet transform to obtain directional subbands of an image. Fractional wavelet decomposition is based on two-channel unbalanced lifting structures whereby it is possible to decompose a given discrete-time signal x[n] sampled with period T into two sub-signals x 1[n] and x 2[n] whose average sampling periods are pT and qT, respectively. Fractions p and q are rational numbers satisfying the condition: 1/p+1/q=1. Filters used in the lifting structure are designed using the Lagrange interpolation formula. 2-d separable and non-separable extensions of the proposed fractional wavelet transform are developed. Using a non-separable unbalanced lifting structure, directional subimages for five different directions are obtained. © 2012 Springer-Verlag.
multirate signal processing
Fractional wavelet transforms
Multirate signal processing
Published Version (Please cite this version)http://dx.doi.org/10.1007/978-3-642-32436-9_9
Showing items related by title, author, creator and subject.
Çetin, A. E. (Elsevier, 1993)In this paper, a new multiresolution wavelet representation for two-dimensional signals is described. This wavelet representation is based on a nonrectangular decomposition of the frequency domain. The decomposition can ...
Erden, F.; Alkar, A. Z.; Cetin, A. E. (Elsevier BV, 2015)Respiratory rate is an essential parameter in many practical applications such as apnea detection, patient monitoring, and elderly people monitoring. In this paper, we describe a novel method and a contact-free multi-modal ...
Leg motion classification with artificial neural networks using wavelet-based features of gyroscope signals Ayrulu-Erdem, B.; Barshan, B. (2011)We extract the informative features of gyroscope signals using the discrete wavelet transform (DWT) decomposition and provide them as input to multi-layer feed-forward artificial neural networks (ANNs) for leg motion ...