我們閱覽關於預測誤差值方法的論文後,發現他們多在追求高資料隱藏的容量以及藏入資料後的圖像品質。在此篇論文中,我們在預測誤差值技術上提出了一個模型。我們利用Fitting Polynomial建造了一個模型並可以解釋Sachnev et al.'s algorithm去支持他,並且在同一個模型下去改良他,得到了更好的資料藏量與圖像品質。
Since we surveyed many papers about the methods based on prediction error, such as Tai et al. (2009), Thodi and Rodriguez (2007), Luo et al. (2010), Sachnev et al. (2009), and Yang et al. (2013), and so on. We found that most of them are pursuing the largest embedding capacity and marked image quality. In this thesis, we not only improve Sachnev et al.'s algorithm but also construct a model for it. We construct a model description for the rhombus method by Fitting Polynomial. Moreover, we got the larger embedding capacity and marked image quality by Fitting Polynomial, too.