Title
On adaptive distortion control in reversible watermarking using modified reversible contrast mapping
Abstract
The use of reversible contrast mapping (RCM) on pair of pixels in images for reversible watermarking (RW) offers a flexible integer transform that leads to high embedding rate at low mathematical complexity and without requiring additional data compression. Mathematically RCM may be interpreted as a form of adaptive linear transformation on pair of pixels that controls distortion and leads to the retention of the structural information of the watermarked image. A generalized form of RCM, analogous to M-ary modulation in communication, is developed here for a set of points and their corresponding embedding spaces are shown geometrically with and without considering distortion control. Then an optimized distortion control framework adaptive to the choice of operating points is considered to improve data hiding capacity under embedding distortion constraint. Simulation results show that the combination of different M-ary approaches i.e. using the points representing the different transformation functions outperform the embedding rate, visual quality and security of the hidden information compared to the existing RCM, difference expansion (DE) and prediction error expansion (PEE) methods during over embedding. Numerical results show that an average of 13 % improvement in visual quality, 25 % improvement in security of the hidden data is achieved at 0.8 bpp embedding rate over existing PEE work. Performance in robustness against common signal processing operations, namely noise addition, smoothing filtering and some form of geometric operation like random bending attack are also studied. All these studies and the effectiveness are demonstrated with a large set of simulation results.
Year
DOI
Venue
2016
10.1007/s11042-015-2710-6
Multimedia Tools Appl.
Keywords
Field
DocType
RW, RCM, M-ary, Kullback-Leibler distance, Adaptive distortion control
Signal processing,Digital watermarking,Computer science,Robustness (computer science),Artificial intelligence,Distortion,Mathematical optimization,Embedding,Pattern recognition,Algorithm,Filter (signal processing),Smoothing,Data compression
Journal
Volume
Issue
ISSN
75
13
1573-7721
Citations 
PageRank 
References 
0
0.34
32
Authors
2
Name
Order
Citations
PageRank
Santi P. Maity140350.37
Hirak Kumar Maity232.44