Reversible Data Embedding without Location Map using Prediction Context Properties

Nguyễn Kim Sao, Đỗ Văn Tuấn, Phạm Văn Ất


This paper presents a new reversible data hiding scheme based on rhombus prediction. Pixels are divided into two sets: dots and crosses. The set of crosses is used as the prediction context for each pixel of the dots. The set of dots is used to embed the message using prediction error expansion. Local variance and depth of the prediction context in the image-value domain ([0, 255] for grayscale images), which are two unchanged attributes in the embedding process, are used to sort the pixels of the set of dots. From this sorted set, we obtain the expandable segments (containing only the expandable pixels). Each expandable segment is marked by two 16-bit integers. Using at most 10 segments, equivelent to 320 extra bits, may be sufficient to cover all expandable bits for hiding data. As a result, the proposed method can improve the embedding capacity as well as the image quality without using the location map as in previous methods.

DOI: 10.32913/rd-ict.vol3.no40.598


Reversible data hiding, pixel sorting, difference expansion, pixel prediction.


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