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Article overview
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Improved CNN Prediction Based Reversible Data Hiding | Yingqiang Qiu
; Wanli Peng
; Xiaodan Lin
; Huanqiang Zeng
; Zhenxing Qian
; | Date: |
4 Jan 2023 | Abstract: | 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. | Source: | arXiv, 2301.01420 | Services: | Forum | Review | PDF | Favorites |
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