Share Email Print
cover

Proceedings Paper

Segmentation-based coding of stereoscopic image sequences
Author(s): Sriram Sethuraman; Mel Siegel; Angel G. Jordan
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

A binocular disparity based segmentation scheme to compactly represent one image of a stereoscopic image pair given the other image was proposed earlier by us. That scheme adapted the excess bitcount, needed to code the additional image, to the binocular disparity detail present in the image pair. This paper addresses the issue of extending such a segmentation in the temporal dimension to achieve efficient stereoscopic sequence compression. The easiest conceivable temporal extension would be to code one of the sequences using an MPEG-type scheme while the frames of the other stream are coded based on the segmentation. However such independent compression of one of the streams fails to take advantage of the segmentation or the additional disparity information available. To achieve better compression by exploiting this additional information, we propose the following scheme. Each frame in one of the streams is segmented based on disparity. An MPEG-type frame structure is used for motion compensated prediction of the segments in this segmented stream. The corresponding segments in the other stream are encoded by reversing the disparity-map obtained during the segmentation. Areas without correspondence in this stream, arising from binocular occlusions and disparity estimation errors, are filled in using a disparity-map based predictive error concealment method. Over a test set of several different stereoscopic image sequences, high perceived stereoscopic image qualities were achieved at an excess bandwidth that is roughly 40% above that of a highly compressed monoscopic sequence. Stereo perception can be achieved at significantly smaller excess bandwidths, albeit with a perceivable loss in the image quality.

Paper Details

Date Published: 22 March 1996
PDF: 10 pages
Proc. SPIE 2668, Digital Video Compression: Algorithms and Technologies 1996, (22 March 1996); doi: 10.1117/12.235437
Show Author Affiliations
Sriram Sethuraman, Carnegie Mellon Univ. (United States)
Mel Siegel, Carnegie Mellon Univ. (United States)
Angel G. Jordan, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 2668:
Digital Video Compression: Algorithms and Technologies 1996
Vasudev Bhaskaran; Frans Sijstermans; Sethuraman Panchanathan, Editor(s)

© SPIE. Terms of Use
Back to Top