High volume reversible watermarking method based on self-adaptive prediction model

Abstract

The invention discloses a high volume reversible watermarking method based on a self-adaptive prediction model. The method comprises a watermark embedding process and a watermark extraction and original image recovery process. The watermark embedding process comprises a design process of a prediction model, and a self-adaptive embedding strategy; and the watermark extraction and original image recovery process is the reverse process of the watermark embedding process. According to the invention, the characteristic of high correlation between neighboring pixels is fully utilized so as to obtain the prediction model with higher prediction performance, so that the high-embedding distortion generated when a prediction error is modified for watermark embedding in a conventional algorithm can be effectively reduced, and besides, through estimating the correlation degree of the four encircling pixels of each pixel to be embedded in a set, the pixels accounting for about three fourth of all the pixels can be enabled to carry 1-2 bit watermarks, thus the capacity is improved.

Description

technical field [0001] The invention relates to the technical field of multimedia signal processing, in particular to a high-capacity reversible watermarking method based on an adaptive prediction model. Background technique [0002] Traditional digital watermarking technology will cause permanent distortion of the host image. However, in some practical applications, a little bit of permanent modification of the host image is not allowed, such as medical, military and judicial fields. Taking medical images as an example, distortion of any kind is not allowed. The acquisition of any medical image requires the support of precision instruments and expensive medical expenses. More importantly, distortion may cause potential misdiagnosis. For example, for an ECG (electrocardiographic) signal graph, any abnormality in the signal curve may be interpreted as a certain pathological feature. Therefore, traditional digital watermarking techniques are not suitable for medical images....

AI Technical Summary

Problems solved by technology

However, if only two adjacent pixels of a certain pixel are used to predict this pixel, the prediction accuracy will not be very high, and the watermark embedding of the obtained prediction error will lead to high embedding distortion

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