A suboptimal embedding algorithm with low complexity for binary data hiding

A novel suboptimal hiding algorithm for binary data based on weight approximation embedding, WAE, is proposed. Given a specified embedding rate, this algorithm exhibits an advantage of efficient binary embedding with reduced embedding complexity. The suboptimal WAE algorithm performs an embedding procedure through a parity check matrix. The optimal embedding based on maximal likelihood algorithm aims to locate the coset leader to minimize the embedding distortion. On the contrary, the WAE algorithm looks for a target vector close to the coset leader in an efficiently iterative manner. Given an linear embedding code C(n, k), the embedding complexity using the optimal algorithm is O(2^k), while the complexity in the suboptimal WAE is reduced to O(sk) where s is the average iterations.