Exploring pixel-value differencing and base decomposition for low distortion data embedding

  • Authors:

  • Nan-I Wu;Kuo-Chen Wu;Chung-Ming Wang

  • Affiliations:

  • Department of Network System, TOKO University, No. 51, Section 2, Syuefu Road, Puzhi City, Chiayi County 61363, Taiwan, ROC;Department of Computer Science and Engineering, National Chung Hsing University, 250 Kuo Kuang Road, Taichung 40227, Taiwan, ROC;Department of Computer Science and Engineering, National Chung Hsing University, 250 Kuo Kuang Road, Taichung 40227, Taiwan, ROC

  • Venue:
  • Applied Soft Computing
  • Year:
  • 2012

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Abstract

This paper presents a low distortion data embedding method using pixel-value differencing and base decomposition schemes. The pixel-value differencing scheme offers the advantage of conveying a large amount of payload, while still maintaining the consistency of an image characteristic after data embedding. We introduce the base decomposition scheme, which defines a base pair for each degree in order to construct a two-base notational system. This scheme provides the advantage of significantly reducing pixel variation encountered due to secret data embedding. We analyze the pixel variation and the expected mean square error caused by concealing with secret messages. The mathematical analysis shows that our scheme produces much smaller maximal pixel variations and expected mean square error while producing a higher PSNR. We evaluate the performance of our method using 6 categories of metrics which allow us to compare with seven other state-of-the-art algorithms. Experimental statistics verify that our algorithm outperforms existing counterparts in terms of lower image distortion and higher image quality. Finally, our scheme can survive from the RS steganalysis attack and the steganalytic histogram attack of pixel-value difference. We conclude that our proposed method is capable of embedding large amounts of a message, yet still produces the embedded image with very low distortion. To the best of our knowledge, in comparison with the current seven state-of-the-art data embedding algorithms, our scheme produces the lowest image distortion while embedding the same or slightly larger quantities of messages.