Stereo image coding: a projection approach.

Abstract

Recently, due to advances in display technology, three-dimensional (3-D) imaging systems are becoming increasingly popular. One way of stimulating 3-D perception is to use stereo pairs, a pair of images of the same scene acquired from different perspectives. Since there is an inherent redundancy between the images of a stereo pair, data compression algorithms should be employed to represent stereo pairs efficiently. This paper focuses on the stereo image coding problem. We begin with a description of the problem and a survey of current stereo coding techniques. A new stereo image coding algorithm that is based on disparity compensation and subspace projection is described. This algorithm, the subspace projection technique (SPT), is a transform domain approach with a space-varying transformation matrix and may be interpreted as a spatial-transform domain representation of the stereo data. The advantage of the proposed approach is that it can locally adapt to the changes in the cross-correlation characteristics of the stereo pairs. Several design issues and implementations of the algorithm are discussed. Finally, we present empirical results suggesting that the SPT approach outperforms current stereo coding techniques.