Coverless Steganography Based on Low Similarity Feature Selection in DCT Domain
L. Tan,
J. Liu,
Y. Zhou
et al.
Abstract:Coverless image steganography typically extracts feature sequences from cover images to map information. Once the extracted features have high similarity, it is challenging to construct a complete mapping sequence set, which places a heavy burden on the underlying storage and computation. In order to improve database utilization while increasing the data-hiding capacity, we propose a coverless steganography model based on low-similarity feature selection in the DCT domain. A mapping algorithm is presented base… Show more
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