We propose a new watermarking method based on quantization index modulation. A concept of initial data loss is introduced in\norder to increase capacity of thewatermarking channel under high intensity additivewhiteGaussian noise.According to the concept\nsome samples in predefined positions are ignored even though this produces errors in the initial stage of watermark embedding.\nThe proposed method also exploits a new form of distribution of quantized samples where samples that interpret ââ?¬Å?0ââ?¬Â and ââ?¬Å?1ââ?¬Â have\ndifferently shaped probability density functions. Compared to well-known watermarking schemes, this provides an increase of\ncapacity under noise attack and introduces a distinctive feature. Two criteria are proposed that express the feature numerically. The\ncriteria are utilized by a procedure for estimation of a gain factor after possible gain attack. Several state-of-the-art quantizationbased\nwatermarking methods were used for comparison on a set of natural grayscale images. The superiority of the proposed\nmethod has been confirmed for different types of popular attacks.
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