• DocumentCode
    1209379
  • Title

    Lossless generalized-LSB data embedding

  • Author

    Celik, Mehmet Utku ; Sharma, Gaurav ; Tekalp, Ahmet Murat ; Saber, Eli

  • Author_Institution
    Electr. & Comput. Eng. Dept., Univ. of Rochester, NY, USA
  • Volume
    14
  • Issue
    2
  • fYear
    2005
  • Firstpage
    253
  • Lastpage
    266
  • Abstract
    We present a novel lossless (reversible) data-embedding technique, which enables the exact recovery of the original host signal upon extraction of the embedded information. A generalization of the well-known least significant bit (LSB) modification is proposed as the data-embedding method, which introduces additional operating points on the capacity-distortion curve. Lossless recovery of the original is achieved by compressing portions of the signal that are susceptible to embedding distortion and transmitting these compressed descriptions as a part of the embedded payload. A prediction-based conditional entropy coder which utilizes unaltered portions of the host signal as side-information improves the compression efficiency and, thus, the lossless data-embedding capacity.
  • Keywords
    data compression; distortion; image coding; multimedia communication; watermarking; capacity distortion curve; compression efficiency; embedded information extraction; embedding distortion; lossless generalized-least significant bit data embedding; multimedia digital watermarking; prediction-based conditional entropy coder; signal compression; Authentication; Biology computing; Biomedical imaging; Data mining; Distortion; Payloads; Propagation losses; Signal processing; Spread spectrum communication; Watermarking; Arithmetic coding; conditional entropy coding; context modeling; data embedding; data hiding; least significant bit (LSB) modification; watermark; Algorithms; Computer Graphics; Computer Security; Data Compression; Image Interpretation, Computer-Assisted; Patents as Topic; Pattern Recognition, Automated; Product Labeling; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2004.840686
  • Filename
    1381493