Fractional cycle spinning via modulated lapped transform for overcomplete image representation

Seisuke Kyochi, Masaaki Ikehara

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper aims to introduce an overcomplete transform based on fractional cycle spinning (FCS). Conventionally, the CS approach of wavelet transforms has been proposed, in order to achieve translation invariance with redundancy, unlike the classical critically sampled wavelet transform. This advantage contributes to efficient image processing, such as image denoising. The proposed FCS generalizes CS and show that richer overcompleteness can be provided by fractional shifts of input signals. For realizing fractional delay, we present the approach based on modulated lapped transforms (MLTs). It is shown that their filter kernels can express arbitrary fractional delay by carefully selecting their window function. In addition, this paper extend the conventional MLT to the dual-tree MLT to improve its poor directional selectivity. Then, an efficient lattice structure for the FCS is described for lower computational complexity. Finally experimental results show FCS can be applied better than the conventional CS in image denoising.

    Original languageEnglish
    Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages2664-2668
    Number of pages5
    ISBN (Print)9781479957514
    DOIs
    Publication statusPublished - 2014 Jan 28

    Keywords

    • Cycle spinning
    • dual-tree cosine modulation
    • modulated lapped transform
    • translation invariance
    • wavelet transform

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition

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