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立体图像残差的变换编码。

Transform coding of stereo image residuals.

机构信息

Image Processing Department, Raytheon Systems Co., Tucson, AZ 85734, USA.

出版信息

IEEE Trans Image Process. 1998;7(6):804-12. doi: 10.1109/83.679421.

Abstract

Stereo image compression is of growing interest because of new display technologies and the needs of telepresence systems. Compared to monoscopic image compression, stereo image compression has received much less attention. A variety of algorithms have appeared in the literature that make use of the cross-view redundancy in the stereo pair. Many of these use the framework of disparity-compensated residual coding, but concentrate on the disparity compensation process rather than the post compensation coding process. This paper studies specialized coding methods for the residual image produced by disparity compensation. The algorithms make use of theoretically expected and experimentally observed characteristics of the disparity-compensated stereo residual to select transforms and quantization methods. Performance is evaluated on mean squared error (MSE) and a stereo-unique metric based on image registration. Exploiting the directional characteristics in a discrete cosine transform (DCT) framework provides its best performance below 0.75 b/pixel for 8-b gray-scale imagery and below 2 b/pixel for 24-b color imagery, In the wavelet algorithm, roughly a 50% reduction in bit rate is possible by encoding only the vertical channel, where much of the stereo information is contained. The proposed algorithms do not incur substantial computational burden beyond that needed for any disparity-compensated residual algorithm.

摘要

立体图像压缩由于新的显示技术和远程呈现系统的需求而引起了越来越多的关注。与单目图像压缩相比,立体图像压缩受到的关注要少得多。文献中出现了各种利用立体对中的视差冗余的算法。其中许多算法使用视差补偿残差编码的框架,但专注于视差补偿过程而不是后补偿编码过程。本文研究了视差补偿产生的残差的专用编码方法。这些算法利用理论上预期和实验观察到的视差补偿立体残差的特性来选择变换和量化方法。性能评估基于均方误差 (MSE) 和基于图像配准的立体专用度量。在离散余弦变换 (DCT) 框架中利用方向特性可以在 8 位灰度图像下提供低于 0.75 b/pixel 的最佳性能,在 24 位彩色图像下提供低于 2 b/pixel 的最佳性能。在小波算法中,通过仅对包含大部分立体信息的垂直通道进行编码,可以将比特率降低约 50%。与任何视差补偿残差算法所需的计算负担相比,所提出的算法不会产生大量额外的计算负担。

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