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Proceedings Paper

Parameterized adaptive predictor for digital image compression based on the differential pulse code modulation
Author(s): M. V. Gashnikov
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Paper Abstract

The adaptive nonlinear predictor is proposed for digital image compression method based on differential pulse code modulation. Greham predictor is parameterized for this. Proposed predictor works in different ways depending on the local image contours. A special feature is offered for estimation the contour direction and intensity in the neighborhood of the current pixel. The parameters of the proposed predictor are calculated by rapid training procedure before the actual compression. This procedure minimizes the sum of absolute values of prediction errors. Theoretical computational complexity of the proposed predictor is shown. Considered predictors are compared in real images by computational experiments. The win of proposed algorithm is demonstrated. In addition, the gain of compression method based on differential pulse code modulation with the proposed predictor against JPEG compression method is demonstrated.

Paper Details

Date Published: 17 March 2017
PDF: 5 pages
Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034110 (17 March 2017); doi: 10.1117/12.2268530
Show Author Affiliations
M. V. Gashnikov, Samara National Research Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 10341:
Ninth International Conference on Machine Vision (ICMV 2016)
Antanas Verikas; Petia Radeva; Dmitry P. Nikolaev; Wei Zhang; Jianhong Zhou, Editor(s)

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