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Proceedings ArticleDOI

Bin Classification Using Temporal Gradient Estimation for Lossless Video Coding

26 Mar 2014-pp 430-430

TL;DR: A novel method for lossless compression of video is proposed that is an efficient replacement for the first method that predicts current pixel using an estimate of deviation from the pixel at same temporal location in the previous frame.

AbstractIn this paper, a novel method for lossless compression of video is proposed. Almost all the prediction based methods reported in literature are of two pass. In the first pass, motion compensated frame is obtained and in the second, some sophisticated method is used to predict the pixels of the current frame. The proposed method is an efficient replacement for the first method that predicts current pixel using an estimate of deviation from the pixel at same temporal location in the previous frame. In this scheme, causal pixels are divided into bins based on the distance between the current and causal pixels. The novelty of the work is in finding out the fixed coefficients of the bins for a particular type of video sequence. The overall performance of the proposed method is same with much lower computational complexity.

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Citations
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Proceedings ArticleDOI
14 Dec 2014
TL;DR: This paper aims to propose a noble method to estimate the auto-regressive(AR) coefficients used by least-square(LS) based predictors by effectively making use of previously estimated AR parameters.
Abstract: This paper aims to propose a noble method to estimate the auto-regressive(AR) coefficients used by least-square(LS) based predictors. Estimation of this LS based predictors is computationally most complex process. This process requires a covariance matrix comprised of chosen causal pixels and also the inverse elements of the same matrix. Computational requirements of this process depends on the number of pixels for which the predictor is trained and also on the order of the predictor. Due to this high complexity, the predictor is not used practically although it provides a high compression ratio. Thus, an alternative algorithm, popularly known as LOPT-3D, was proposed in literature. However, the number of pixels required for the estimation of AR parameters are still large, and thereby, making it impracticable for real-time implementations. The proposed method overcomes this limitation by effectively making use of previously estimated AR parameters.

Cites background from "Bin Classification Using Temporal G..."

  • ...In [11], the author have estimated the pixel based on its deviation from the causal pixels in the previous frame....

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