Title
Watermarking With Flexible Self-Recovery Quality Based on Compressive Sensing and Compositive Reconstruction
Abstract
This paper proposes a novel watermarking scheme with flexible self-recovery quality. The embedded watermark data for content recovery are calculated from the original discrete cosine transform (DCT) coefficients of host image and do not contain any additional redundancy. When a part of a watermarked image is tampered, the watermark data in the area without any modification still can be extracted. If the amount of extracted data is large, we can reconstruct the original coefficients in the tampered area according to the constraints given by the extracted data. Otherwise, we may employ a compressive sensing technique to retrieve the coefficients by exploiting the sparseness in the DCT domain. This way, all the extracted watermark data contribute to the content recovery. The smaller the tampered area, the more available watermark data will result in a better quality of recovered content. It is also shown that the proposed scheme outperforms previous techniques in general.
Year
DOI
Venue
2011
10.1109/TIFS.2011.2159208
IEEE Transactions on Information Forensics and Security
Keywords
Field
DocType
flexible self-recovery quality,embedded watermark data,tampered area,dct domain,available watermark data,compositive reconstruction,host image,compressive sensing,original coefficient,content recovery,better quality,watermark data,compressed sensing,redundancy,data mining,digital watermark,discrete cosine transform,image reconstruction,digital watermarking,watermarking
Iterative reconstruction,Computer vision,Self recovery,Digital watermarking,Pattern recognition,Computer science,Discrete cosine transform,Watermark,Redundancy (engineering),Artificial intelligence,Discrete cosine transforms,Compressed sensing
Journal
Volume
Issue
ISSN
6
4
1556-6013
Citations 
PageRank 
References 
48
1.39
26
Authors
4
Name
Order
Citations
PageRank
Xinpeng Zhang12541174.68
Zhenxing Qian252539.26
Yanli Ren324724.83
Guorui Feng439422.42