ADAPTIVE DATA HIDING USING WAVELET DOMAIN SINGULAR VALUE DECOMPOSITION

Author(s):  
P. BAO ◽  
X. MA
2011 ◽  
Vol 271-273 ◽  
pp. 536-540
Author(s):  
Ying Tian ◽  
Xue Song Peng ◽  
Yun Fei Wei

This paper presents a blind watermarking algorithm based on quantization index modulation (QIM) and singular value decomposition (SVD) in the wavelet domain. Obtain approximation sub band of the wavelet domain coefficient matrix by performing a wavelet transform on host image. The QIM technique determines the quantization step for each embedding block. The SVD technique is modified the SVs of each embedding block. The watermark encrypted by a chaos sequence generated by Lorenz chaotic system is embedded the host image. The experiments show that this paper presented algorithm in various attacks against the image has good robustness especially for against geometric attacks and image compression.


2013 ◽  
pp. 400-434
Author(s):  
Victor Pomponiu ◽  
Davide Cavagnino ◽  
Alessandro Basso ◽  
Annamaria Vernone

Information hiding techniques are acquiring an always increasing importance, due to the widespread diffusion of multimedia contents. Several schemes have been devised in the fields of steganography and digital watermarking, exploiting the properties of different domains. In this chapter, the authors focus on the SVD transform, with the aim of providing an exhaustive overview (more than 100 papers are analyzed) on those steganography and watermarking techniques leveraging on the important properties of such a transform. The large number of algorithms operating in the image, video and audio contexts is first classified by means of a general approach, then analyzed, to highlight the advantages and disadvantages of each method. The authors also give a detailed discussion about the applicability of each reviewed and compared data hiding scheme, in order to identify the most appropriate candidates for practical applications.


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