Paper
18 October 1999 Object-driven block-based algorithm for the compression of stereo image pairs
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Abstract
In this paper, we propose a novel object driven, block based algorithm for the compression of stereo image pairs. The algorithm effectively combines the simplicity and adaptability of the existing block based stereo image compression techniques with an edge/contour based object extraction technique to determine appropriate compression strategy for various areas of the right image. Extensive experiments carried out support that significant improvements of up to 20% in compression ratio can be achieved by the proposed algorithm, compared with the existing stereo image compression techniques. Yet the reconstructed image quality is maintained at an equivalent level in terms of PSNR values. In terms of visual quality, the right image reconstructed by the proposed algorithm does not incur any noticeable effect compared with the outputs of the best algorithms. The proposed algorithm performs object extraction and matching between the reconstructed left frame and the original right frame to identify those objects that match but are displaced by varying amounts due to binocular parallax. Different coding strategies are then applied separately to internal areas and the bounding areas for each identified object. Based on the mean squared matching error of the internal blocks and a selected threshold, a decision is made whether or not to encode the predictive errors inside these objects. The output bit stream includes entropy coding of object disparity, block disparity and possibly some errors, which fail to meet the threshold requirement in the proposed algorithm.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Eran Anusha Edirisinghe, Jianmin Jiang, and Helmut E. Bez "Object-driven block-based algorithm for the compression of stereo image pairs", Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); https://doi.org/10.1117/12.365840
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Cited by 1 scholarly publication.
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KEYWORDS
Image compression

Computer programming

Reconstruction algorithms

Algorithm development

Image quality

Visualization

Data compression

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