Yingqiang Qiu | Searcharxiv

arXiv2023

Improved CNN Prediction Based Reversible Data Hiding

This letter proposes an improved CNN predictor (ICNNP) for reversible data hiding (RDH) in images, which consists of a feature extraction module, a pixel prediction module, and a complexity prediction module. Due to predicting the complexity of each pixel with the ICNNP during the embedding process, the proposed method can achieve superior performance than the CNN predictor-based method. Specifically, an input image does be first split into two different sub-images, i.e., the "Dot" image and the "Cross" image. Meanwhile, each sub-image is applied to predict another one. Then, the prediction errors of pixels are sorted with the predicted pixel complexities. In light of this, some sorted prediction errors with less complexity are selected to be efficiently used for low-distortion data embedding with a traditional histogram shift scheme. Experimental results demonstrate that the proposed method can achieve better embedding performance than that of the CNN predictor with the same histogram shifting strategy.

cs.MM↗

arXiv2022

High-Capacity Framework for Reversible Data Hiding in Encrypted Image Using Pixel Predictions and Entropy Encoding

While the existing vacating room before encryption (VRBE) based schemes can achieve decent embedding rate, the payloads of the existing vacating room after encryption (VRAE) based schemes are relatively low. To address this issue, this paper proposes a generalized framework for high-capacity RDHEI for both VRBE and VRAE cases. First, an efficient embedding room generation algorithm (ERGA) is designed to produce large embedding room by using pixel prediction and entropy encoding. Then, we propose two RDHEI schemes, one for VRBE, another for VRAE. In the VRBE scenario, the image owner generates the embedding room with ERGA and encrypts the preprocessed image by using the stream cipher with two encryption keys. Then, the data hider locates the embedding room and embeds the encrypted additional data. In the VRAE scenario, the cover image is encrypted by an improved block modulation and permutation encryption algorithm, where the spatial redundancy in the plain-text image is largely preserved. Then, the data hider applies ERGA on the encrypted image to generate the embedding room and conducts data embedding. For both schemes, the receivers with different authentication keys can respectively conduct error-free data extraction and/or error-free image recovery. The experimental results show that the two proposed schemes outperform many state-of-the-art RDHEI arts. Besides, the schemes can ensure high security level, where the original image can be hardly discovered from the encrypted version before and after data hiding by the unauthorized user.

cs.MM↗