A greedy steganographic SMVQ approach of greedy-USBIRDS using secret bits for image-block repairing based on differences

Wei Jen Wang, Cheng Ta Huang, Shiau Rung Tsuei, Shiuh Jeng Wang

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Steganography conceals the secret data into cover media to avoid detection, such that no one suspects the existence of the embedded secret data. The existing VQ-based and SMVQ-based steganographic methods can only provide the same level of visual quality of what the VQ/SMVQ compression method can offer. 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 approach 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 such as Baboon. 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. All the experimental results indicate that, this study makes significant contributions to the area of VQ-based and SMVQ-based steganography, especially for its excellent stego-image quality and its ability to handle complex cover images very well.

Original languageEnglish
Pages (from-to)14895-14916
Number of pages22
JournalMultimedia Tools and Applications
Volume75
Issue number22
DOIs
StatePublished - 1 Nov 2016

Keywords

  • Information hiding
  • Side-match vector quantization (SMVQ)
  • Steganography

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