A suboptimal embedding algorithm with low complexity for binary data hiding

Abstract

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(2k), while the complexity in the suboptimal WAE is reduced to O(sk) where s is the average iterations.