Syndrome trellis codes based on minimal span generator matrix

Abstract

To improve the embedding efficiency of steganography, syndrome coding based on the coding theory has attracted many researchers’ attentions. In this paper, we make use of the relationship between syndrome coding for minimizing additive distortion and maximum likelihood decoding for linear codes to analyze the main parameters of convolutional codes which influence the embedding efficiency. And, the new syndrome trellis codes based on minimal span generator matrix is proposed. It can be considered an alternative construction of the state-of-the-art syndrome trellis codes (STCs) proposed by Filler and Fridrich recently. Experimental results show that the proposed scheme owns the same embedding performance to STCs and achieve the reduced time complexity and storage requirement meanwhile.