Paper
19 January 2006 Shape adaptive integer transform for coding arbitrarily shaped objects in H.264/AVC
Author Affiliations +
Proceedings Volume 6077, Visual Communications and Image Processing 2006; 60770C (2006) https://doi.org/10.1117/12.642320
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
The use of shape-adaptive transforms is a popular approach for coding arbitrarily shaped objects in image/video coding due to their adaptability at object edges and low complexity. In this respect shape adaptive DCT (SA-DCT) and shape adaptive DWT (SA-DWT) have been proposed in previous literature. The Integer Transform (IT), a derivative of the 4x4 DCT, has been adopted in the latest H.264/AVC standard for coding image blocks in residual data (texture). The associated integer arithmetic guarantees fast and accurate coding/decoding. In this paper, we propose a novel Shape Adaptive Integer Transform (SA-IT) which can be effectively used in future for enabling arbitrary shaped object coding in H.264. Though Integer Transforms are a derivative of 4x4 DCTs, in H.264, to maintain integer arithmetic capability, the post-and pre-scaling factors of transform process are integrated into the forward and inverse quantiser stages respectively for reducing the total number of multiplications and avoiding the loss of accuracy. Thus SA-IT considerably differs from SA-DCT and calls for novel design and implementation considerations based on combining those merits of both SA-DCT and IT. We provide theoretical proofs and support them with experimental justifications.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiongwen Li, Eran Edirisinghe, and Helmut Bez "Shape adaptive integer transform for coding arbitrarily shaped objects in H.264/AVC", Proc. SPIE 6077, Visual Communications and Image Processing 2006, 60770C (19 January 2006); https://doi.org/10.1117/12.642320
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Cited by 3 scholarly publications.
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KEYWORDS
Information technology

Image compression

Quantization

Image quality

Computer programming

Video coding

Visualization

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