An Image Adaptive Steganogaphy Algorithm Based on Sparse Representation and Entropy
- Chunmei Yu, Jianjun Wang
- Corresponding Author
- Chunmei Yu
Available Online October 2013.
- https://doi.org/10.2991/isca-13.2013.37How to use a DOI?
- sparse representation; entropy; image adaptive steganography; steganalysis
- According to the image processing theory, complex texture image regions have larger entropy values, an adaptive steganography algorithm in the sparse domain is proposed here. The algorithm first divides an image into nonoverlapping image blocks, then computes the entropy of each block and chooses the mean of all entropies as a threshold. Image blocks whose entropy is higher than the threshold are selected for sparse decomposition as complex texture image regions. The secret message is embedded into the decomposition coefficients, and then the stego image is reconstructed with modified coefficients. The experimental results prove that, given the same payload, the proposed adaptive algorithm has a better performance against the steganalyzer.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Chunmei Yu AU - Jianjun Wang PY - 2013/10 DA - 2013/10 TI - An Image Adaptive Steganogaphy Algorithm Based on Sparse Representation and Entropy BT - 2013 International Conference on Information Science and Computer Applications (ISCA 2013) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/isca-13.2013.37 DO - https://doi.org/10.2991/isca-13.2013.37 ID - Yu2013/10 ER -