Advanced Search
Volume 36 Issue 6
Jul.  2014
Turn off MathJax
Article Contents
Qiu Ying-Qiang, Yu Lun. Adaptive Reversible Image Watermarking Method Based on Integer Transform[J]. Journal of Electronics & Information Technology, 2014, 36(6): 1278-1284. doi: 10.3724/SP.J.1146.2013.01528
Citation: Qiu Ying-Qiang, Yu Lun. Adaptive Reversible Image Watermarking Method Based on Integer Transform[J]. Journal of Electronics & Information Technology, 2014, 36(6): 1278-1284. doi: 10.3724/SP.J.1146.2013.01528

Adaptive Reversible Image Watermarking Method Based on Integer Transform

doi: 10.3724/SP.J.1146.2013.01528 cstr: 32379.14.SP.J.1146.2013.01528
  • Received Date: 2013-10-08
  • Rev Recd Date: 2014-01-08
  • Publish Date: 2014-06-19
  • To ensure the quality of watermarked image and improve the embedding capacity of watermarkings, an adaptive image reversible watermarking method based on interger transform is proposed in this paper, which defines a new generalized integer transform algorithm. Through the use of the method the image blocks of arbitrary sized are transformed, producing certain redundancy data that can be used for watermarking embedding. In addition, the parameter m used for integer transform is adaptively selected according to the variance of every image block, hence allowing for embedding more data bits into the smooth blocks while avoiding large distortion generated by complex ones, and thus the algorithm ensures a higher embedding capacity and better quality of watermarked image. Compared with similar algorithms, the experimental results show that the proposed method has larger maximal embedding capacity and taking Lena as a host image, the real payload can reach up to 2.36 bpp. The proposed integer transform algorithm is simple; through adaptively interger transforming and data embedding, the quality of watermarked image can be assured and the method offers a large real payload.
  • loading
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (2406) PDF downloads(849) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return