Title :
Robust Image Data Hiding Using Geometric Mean Quantization
Author :
Akhaee, Mohammad Ali ; Ghaemmaghami, Shahrokh ; Nikooienejad, Amir ; Marvasti, Farokh
Abstract :
In this paper, a novel quantization based watermarking method is proposed. For blind detection, a set of nonlinear convex functions based on geometric mean are investigated. In order to achieve minimum distortion, the optimum function set is found. The algorithm is implemented on the approximation coefficients of wavelet transform for natural images. In order to make the algorithm more robust and imperceptible, a new transform domain called Point to Point Graph (PPG), which converts a 1-D signal to a 2-D one, has been used. The error probability of the proposed scheme is analytically investigated. Simulation results show that this algorithm has great robustness against common attacks such as AWGN, JPEG and rotation in comparison with recent methods presented so far.
Keywords :
approximation theory; data encapsulation; error statistics; graph theory; image coding; watermarking; wavelet transforms; approximation coefficient; blind detection; error probability; geometric mean quantization; nonlinear convex function; point to point graph; quantization based watermarking; robust image data hiding; wavelet transform; AWGN; Approximation algorithms; Data encapsulation; Error probability; Image converters; Nonlinear distortion; Quantization; Robustness; Watermarking; Wavelet transforms;
Conference_Titel :
Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4244-4148-8
DOI :
10.1109/GLOCOM.2009.5426109