1999
DOI: 10.1109/76.744280
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Video compression using matching pursuits

Abstract: Abstract-The use of matching pursuit (MP) to code video using overcomplete Gabor basis functions has recently been introduced. In this paper, we propose new functionalities such as SNR scalability and arbitrary shape coding for video coding based on matching pursuit. We improve the performance of the baseline algorithm presented earlier by proposing a new search and a new position coding technique. The resulting algorithm is compared to the earlier one and to DCT-based coding.

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Cited by 72 publications
(87 citation statements)
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References 12 publications
(34 reference statements)
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“…In our study, we focus on developing SNR scalability algorithms at low bit rates in a hybrid motion-compensation video coding system in which the frame residuals are encoded using matching pursuits. Certain matching pursuit SNR-scalable schemes have been proposed in (Al-Shaykh et al, 1999;Vleeschouwer & Macq, 2000). An FGS produces a continuous bit-stream with increasing PSNR for a wide range of bit rates.…”
Section: Scalable Video Codingmentioning
confidence: 99%
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“…In our study, we focus on developing SNR scalability algorithms at low bit rates in a hybrid motion-compensation video coding system in which the frame residuals are encoded using matching pursuits. Certain matching pursuit SNR-scalable schemes have been proposed in (Al-Shaykh et al, 1999;Vleeschouwer & Macq, 2000). An FGS produces a continuous bit-stream with increasing PSNR for a wide range of bit rates.…”
Section: Scalable Video Codingmentioning
confidence: 99%
“…Thus, the matching pursuit update algorithm cannot be used in video encoding. Instead, the proposed approach in (Neff & Zakhor, 1997;Al-Shaykh et al, 1999) divides a residual into blocks and, at each iteration, the matching pursuit algorithm is applied to the block with the highest energy. This approach is both simple and efficient, and has been implemented in many MP-based video codecs.…”
Section: Matching Pursuit Algorithm and Atom Extractionmentioning
confidence: 99%
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