Steganographic Greedy Algorithms for Data Hiding Based on Differences Under SMVQ

Abstract

In this study, we present the idea of using secret bits to repair SMVQ-compressed images. The idea can be viewed as the optimization problem of Using Secret Bits for Image-block Repairing based on Differences under SMVQ (USBIRDS). We propose a novel algorithm named Greedy-USBIRDS to find a near optimal solution for the USBIRDS problem. The experimental results show that, the proposed method provides excellent stego-image quality and large embedding capacity, in particular for complex cover images. While compared with Chen and Lin’s steganographic method, which is the known best method based on VQ/SMVQ, the proposed method achieves about 53 % more dB of PSNR of the stego-image quality and about 4.2 % more bits of the embedding capacity on average.