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A novel reversible ternary embedding algorithm based on modified full context prediction errors

Li, Li; Chang, Chinchen; Karunanithi, Bharanitharan; Liu, Yanjun


We propose a high capacity reversible ternary embedding-watermarking algorithm based on a modification of full-context-prediction-errors (MFCPE) wherein the binary bit stream is converted to the ternary stream then error histogram shifting is utilized to embed the ternary stream. Unlike the existing predictor methods, we provide a full context prediction with a modification of each pixel at most by 1, which significantly reduces distortion. Experimental results confirm that the proposed...[Show more]

CollectionsANU Research Publications
Date published: 2017
Type: Conference paper
Source: 2016 IEEE International Conference on Signal and Image Processing, ICSIP 2016
DOI: 10.1109/SIPROCESS.2016.7888318


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