Reversible watermarking is a kind of digital watermarking which is able to recover the original image exactly as well\nas extracting hidden message. Many algorithms have aimed at lower image distortion in higher embedding capacity.\nIn the reversible data hiding, the role of efficient predictors is crucial. Recently, adaptive predictors using least square\napproach have been proposed to overcome the limitation of the fixed predictors. This paper proposes a\nnovel reversible data hiding algorithm using least square predictor via least absolute shrinkage and selection\noperator (LASSO). This predictor is dynamic in nature rather than fixed. Experimental results show that the\nproposed method outperforms the previous methods including some algorithms which are based on the\nleast square predictors.
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