Low-complexity Matrix Embedding Using an Efficient Iterative Search Strategy

This study proposes a novel suboptimal embedding algorithm for binary messages based on a lowweight search embedding (LWSE) strategy. The suboptimal LWSE strategy involves using algorithm to perform an embedding procedure by using a parity check matrix. The optimal embedding algorithm, which is based on the maximun likelihood (ML) algorithm, aims to locate the coset leader and minimize embedding distortion. The optimal embedding based on linear codes can achieve high embedding efficiency but incurs high computation. Conversely, the LWSE does not need to locate the coset leader, but instead requires suboptimal object. Because its corresponding weight remains close to that of the coset leader, the algorithm proceeds in an efficiently iterative manner. When using the optimal ML algorithm for a situation involving the highest operation complexity, the operation complexity of the suboptimal LWSE is linearly proportional to the number of code dimension. Key-Words: suboptimal embedding algorithm, data hiding, digital watermarking, informed coding, informed embedding, maximun likelihood algorithm.