An efficient histogram-based index mapping mechanism for reversible data hiding in VQ-compressed images

High Capacity Reversible Data Hiding for VQ-Compressed Images Based on Difference Transformation and Mapping Technique

“…To further demonstrate the effectiveness and superiority of our proposed joint method, we also compared the embedding capacity, bitrate and embedding rate between our joint method and other existing methods [2], [3], [19]- [23]. It should be noted that, in these experiments, two strategies of the proposed joint method based on Case 1 and Case 2 are performed, respectively.…”

“…It should be pointed out that the mapping table should be sent to the receiver as the auxiliary information. Inspired by reference [3], in this paper, we used the scheme that is to embed the mapping table before the secret data through using a generic mapping table, followed by embedding the secret data by using the specific mapping table. Here, the specific mapping table means it constructed based on the Standardindex based histogram or Difference-index based histogram of each image, and the generic mapping table means a predefined and pre-shared mapping table.…”

“…It is based on a declustering strategy and utilizes the local spatial characteristics of the VQ-compressed images. Later, some other researchers also developed [3], [19], [22], [30]- [34]. In [22], [31], [32], index mapping schemes were based on the referred counts of the indices, and the embedding capacities are low.…”

“…In [19], [29], [30], [34], the index mapping schemes were based on the sidematch prediction, but they failed to use it in an efficient way. Scheme [3] also used the SMVQ and LAS schemes to explore the redundancy, followed by constructing an efficient index mapping mechanism based on the theory of Huffman coding, and finally they obtained a much higher embedding capacity and better bitrate than the previous methods.…”

“…In [43], the secret data is embedded by using the difference values between the current standard-index and its left or upper neighboring indices. In particular, the histogram-based index mapping mechanism proposed by [3] achieved a much higher embedding capacity than that of past methods. Obviously, those schemes exploit various types of indirect correlations to achieve a good performance in embedding capacity and just only explore the redundancy room in the standard-index table.…”