Paper
17 March 2017 Parameterized adaptive predictor for digital image compression based on the differential pulse code modulation
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Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 1034110 (2017) https://doi.org/10.1117/12.2268530
Event: Ninth International Conference on Machine Vision, 2016, Nice, France
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.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. V. Gashnikov "Parameterized adaptive predictor for digital image compression based on the differential pulse code modulation", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034110 (17 March 2017); https://doi.org/10.1117/12.2268530
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KEYWORDS
Image compression

Modulation

Image processing

Switching

Prototyping

Remote sensing

Computer programming

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