Title

Video compression using spatiotemporal regularity flow

Authors

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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