Steganographic greedy algorithms for data hiding based on differences under SMVQ

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

Research output: Contribution to journalConference articlepeer-review


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.


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


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