Proceedings ArticleDOI
Optimal slope bin classification in gradient adjusted predictor for lossless compression of medical images
Anil Kumar Tiwari,Rohitashw Kumar +1 more
- Vol. 2, pp 281-284
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TLDR
Simulation results, for medical images, using optimal slope bins and associated predictors show a significant better compression performance as compared to the other methods such as GAP and edge-directed prediction (EDP) method.Abstract:
Gradient adjusted predictor (GAP) uses seven fixed range of slope quantization bins and different predictors associated with each bin, for prediction of pixels of all kinds of images. Criteria for range of slope in the bins and associated predictors are not reported in the literature. This paper presents a technique for slope quantization bins which are optimum for a given set of images. It also presents a technique for finding a statistically optimal predictor for a given range of slope bin. Simulation results, for medical images, using optimal slope bins and associated predictors show a significant better compression performance as compared to the other methods such as GAP and edge-directed prediction (EDP) method. The proposed method and GAP has same order of computational complexity while EDP is computationally much expensive.read more
Citations
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Lossless image coding via adaptive linear prediction and classification
TL;DR: In this article, a single-pass adaptive algorithm that uses context classification and multiple linear predictors, locally optimized on a pixel-by-pixel basis, is proposed to obtain a compression ratio comparable to CALIC while improving on some images.
Proceedings ArticleDOI
Least-Squares Based Switched Adaptive Predictors for Lossless Video Coding
TL;DR: A context-based predictive coding method for lossless compression of video using a model to estimate level of activity in the prediction context of a pixel in terms of slope and a LS based method to find switched predictors to be associated with the various bins.
Proceedings ArticleDOI
A Switched Predictive Coding Method for Lossless Video Coding
Anil Kumar Tiwari,Rajeev Kumar +1 more
TL;DR: Simulation results show that the application of the set of the predictors results in competitive performance with the LOPT - one of the best methods in terms of achievable compression ratio.
References
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Proceedings Article
Lossless image coding via adaptive linear prediction and classification
TL;DR: In this article, a single-pass adaptive algorithm that uses context classification and multiple linear predictors, locally optimized on a pixel-by-pixel basis, is proposed to obtain a compression ratio comparable to CALIC while improving on some images.
Proceedings ArticleDOI
A switched adaptive predictor for lossless compression of high resolution images
TL;DR: This work proposes a statistically valid sixth order predictor, which is used for predicting pixels under various slope conditions in the GAP frame work, and shows that the average entropy of the residual images is reduced significantly, when applied on high resolution images.