Quantization Based Watermarking Approach with Gain Attack Recovery

A new Quantization Index Modulation-based watermarking approach is proposed in this paper. With the aim to increase capacity of the watermarking channel with noise we propose Initial Data Loss during quantization for some samples in pre-defined positions. Also, the proposed approach exploits a new form of distribution of quantized samples where samples that interpret "0" and "1" have differently shaped probability density functions. This creates a distinctive feature which is expressed numerically using one out of two proposed criteria. The criteria are utilized by a procedure for recovery after possible Gain Attack. Several state of the art quantization-based watermarking methods were used for comparison on a set of natural grayscale images. The superiority of the proposed method has been confirmed for different types of popular attacks.