A high-fidelity reversible watermark embedding method

Abstract

The invention relates to a high-fidelity reversible watermark embedding method including a watermark embedding process, watermark extraction, and a raw image recovery process. During watermark embedding, pixels of a carrier image are divided into two pixel sets, A and B, which are not overlapped. The pixels belonging to the pixel set A are subjected to embedding first, then modified pixels in the pixel set A are used to predict pixels belonging to the pixel set B, and information embedding is conducted on the pixels in the pixel set B. For any to-be-predicted pixel p, n pixels surrounding the pixel p form a neighborhood of the pixel p, and after the values of all the pixels in the neighborhood are sorted, the maximum and the minimum in the neighborhood closest to the pixel p are used to predict the pixel p. As the pixels closest to the pixel p are used for predicting the pixel p, the prediction performance is greatly improved. The larger n is, the more precise the prediction can be, and the lower the capacity is accordingly. The smaller n is, the less precise the prediction is, and the higher the capacity is accordingly. With determined capacity, the method searches for the optimal embedding point with the least loss, thereby improving embedding distortion effectively.

Description

technical field [0001] The invention belongs to the field of multimedia signal processing, in particular to a high-fidelity reversible watermark embedding method. 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 sophisticated instruments and expensive medical expenses. More importantly, distortion may cause potential misdiagnosis. For example, for an ECG (electrocardiographic) signal diagram, 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. [0003] A technique called rever...

AI Technical Summary

Problems solved by technology

In fact, the number of pixels adjacent to the peak point is second only to the number of peak points. Embedding the watermark on the peak point will inevitably translate the pixels near the peak point, which will inevitably move a large number of pixels, resulting in a larger embedding distortion

[0014] In summary, in the algorithm of Qu et al., only using n pixels to the right of p to predict p cannot accurately estimate the local complexity of p, so the prediction performance is weaker than that of the Sachnev method

In addition, the method of Ou et al. is still the same as the traditional method based on grayscale translation. Selecting the peak point as the embedding point will inevitably translate a large number of pixels adjacent to the peak point, so it will cause a large embedding distortion.

Images