An Image Adaptive Steganogaphy Algorithm Based on Sparse Representation and Entropy

DOI

10.2991/isca-13.2013.37How to use a DOI?

Keywords

sparse representation; entropy; image adaptive steganography; steganalysis

Abstract

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of 2013 International Conference on Information Science and Computer Applications
PB  - Atlantis Press
SP  - 214
EP  - 219
SN  - 1951-6851
UR  - https://doi.org/10.2991/isca-13.2013.37
DO  - 10.2991/isca-13.2013.37
ID  - Yu2013/10
ER  -