Abstract
In 2012, Lee et al. proposed an interpolation enlargement technique using neighboring pixels as the base on which secret messages are embedded in enlarged interpolated pixels. This method can effectively predict the pixel between two adjacent pixels so as to reduce the distortion caused by the hidden secret messages. However, in this study we found that while Lee et al.’s neighboring pixel prediction method can successfully achieve a predictive value, embedded secret messages of different sizes will cause great distortion when a large secret message is hidden in the predicted value. Therefore, the purpose of our research is to determine how to process secret messages in advance to reduce the harm caused by embedding. We propose a secret message reduction strategy that changes positive secret messages to both positive and negative to decrease their values and thereby reduce stego-image distortion.
Highlights
The information age has recently witnessed an unprecedented increase in digital media transfer
This study focuses on secret message sharing
Data hiding is divided into non-reversible data hiding (Non-RHD) and reversible data hiding (RDH), depending on whether a stegoimage can be restored to the original image
Summary
The information age has recently witnessed an unprecedented increase in digital media transfer. Researchers have developed data hiding techniques to embed secret messages in media to successfully transfer and protect confidential information. Data hiding has been widely used in many applications, including secret message sharing, image authentication, ownership assertion, tamper detection, and watermarking. Data hiding is divided into non-reversible data hiding (Non-RHD) and reversible data hiding (RDH), depending on whether a stegoimage can be restored to the original image. When a stego-image cannot be restored to the original image after the extraction of secret messages, it is known as a non-RHD technique. An RDH technique can restore a stego-image to the original image, enabling the reuse of images. The reuse of images comes at the expense of embedding capacity. A major focus of RDH research is how to improve the embedding capacity while maintaining image restorability
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