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MEDIAFORENSICS
2010

Minimizing embedding impact in steganography using trellis-coded quantization

9 years 26 days ago
Minimizing embedding impact in steganography using trellis-coded quantization
In this paper, we propose a practical approach to minimizing embedding impact in steganography based on syndrome coding and trellis-coded quantization and contrast its performance with bounds derived from appropriate rate-distortion bounds. We assume that each cover element can be assigned a positive scalar expressing the impact of making an embedding change at that element (single-letter distortion). The problem is to embed a given payload with minimal possible average embedding impact. This task, which can be viewed as a generalization of matrix embedding or writing on wet paper, has been approached using heuristic and suboptimal tools in the past. Here, we propose a fast and very versatile solution to this problem that can theoretically achieve performance arbitrarily close to the bound. It is based on syndrome coding using linear convolutional codes with the optimal binary quantizer implemented using the Viterbi algorithm run in the dual domain. The complexity and memory requireme...
Tomás Filler, Jan Judas, Jessica J. Fridric
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2010
Where MEDIAFORENSICS
Authors Tomás Filler, Jan Judas, Jessica J. Fridrich
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