High-fidelity reversible information hiding method and device based on prediction error value sorting

Abstract

The invention relates to a high-fidelity reversible information hiding method and device based on prediction error value sorting. According to the method, a method based on prediction error extensionand a method based on pixel value sorting are combined, and the defect that prediction error correlation is not utilized in a traditional method is overcome. According to the method, a carrier image is divided into non-overlapping image blocks with the same size, and local correlation between prediction errors in the blocks is considered; for each image block, prediction errors are sorted first, and then the maximum value and the minimum value therein are predicted and modified to embed secret information. According to the method, image redundancy is better utilized, good embedding performanceis achieved, embedding and extraction of secret information in the grayscale image can be achieved, an original image is recovered in a lossless mode, and the method is a high-fidelity reversible information hiding algorithm with good performance and can be used in the fields of secret communication, copyright protection and the like.

Description

technical field [0001] The invention relates to the technical field of information hiding, and the main content is the design of a reversible information hiding method for an invisible, spatial domain, and non-compressed grayscale image. Reversible information hiding technology can not only extract the embedded secret information, but also restore the original carrier data without any distortion. The research focus of this technology is mainly on how to reduce the embedding distortion. Specifically, this method combines the method based on prediction error expansion with the method based on pixel value ranking, which improves the shortcomings of traditional methods that do not take advantage of the correlation of prediction errors. This method divides the cover image into non-overlapping image blocks of the same size, and considers the local correlation between prediction errors in the blocks. For each image patch, the prediction errors are first sorted, and then the maximum...

AI Technical Summary

Problems solved by technology

For methods based on two-dimensional prediction error histogram expansion, such as pairwise PEE, only the correlation between two adjacent prediction errors is considered, and the histogram modification method is designed heuristically, without considering the specific image content. Achieving better adaptive embedding

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