Video compression using spatiotemporal regularity flow

    Authors

    O. Alatas; O. Javed;M. Shah

    Comments

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    Abbreviated Journal Title

    IEEE Trans. Image Process.

    Keywords

    image and video multi-resolution processing (2-MRP); wavelet based video; coding (1-COD-WAVV); Computer Science, Artificial Intelligence; Engineering, Electrical &; Electronic

    Abstract

    We propose a new framework in wavelet video coding to improve the compression rate by exploiting the spatiotemporal regularity of the data. A sequence of images creates a spatiotemporal volume. This volume is said to be regular along the directions in which the pixels vary the least, hence the entropy is the lowest. The wavelet decomposition of regularized data results in a fewer number of significant coefficients, thus yielding a higher compression rate. The directions of regularity of an image sequence depend on both its motion content and spatial structure. We propose the representation of these directions by a 3-D vector field, which we refer to as the spatiotemporal regularity flow (SPREF). SPREF uses splines to approximate the directions of regularity. The compactness of the spline representation results in a low storage overhead for SPREF, which is a desired property in compression applications. Once SPREF directions are known, they can be converted into actual paths along which the data is regular. Directional decomposition of the data along these paths can be further improved by using a special class of wavelet basis called the 3-D orthonormal bandelet basis. SPREF-based video compression not only removes the temporal redundancy, but it also compensates for the spatial redundancy. Our experiments on several standard video sequences demonstrate that the proposed method results in higher compression rates as compared to the standard wavelet based compression.

    Journal Title

    Ieee Transactions on Image Processing

    Volume

    15

    Issue/Number

    12

    Publication Date

    1-1-2006

    Document Type

    Article

    Language

    English

    First Page

    3812

    Last Page

    3823

    WOS Identifier

    WOS:000242362900017

    ISSN

    1057-7149

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