Quantization based watermarking methods against valumetric distortions

Most of the quantization based watermarking algorithms are very sensitive to valumetric distortions, while these distortions are regarded as common processing in audio/video analysis. In recent years, watermarking methods which can resist this kind of distortions have attracted a lot of interests. But still many proposed methods can only deal with one certain kind of valumetric distortion such as amplitude scaling attack, and fail in other kinds of valumetric distortions like constant change attack, gamma correction or contrast stretching. In this paper, we propose a simple but effective method to tackle all the three kinds of valumetric distortions. This algorithm constructs an invariant domain first by spread transform which satisfies certain constraints. Then an amplitude scale invariant watermarking scheme is applied on the constructed domain. The validity of the approach has been confirmed by applying the watermarking scheme to Gaussian host data and real images. Experimental results confirm its intrinsic invariance against amplitude scaling, constant change attack and robustness improvement against nonlinear valumetric distortions.