US 11,321,796 B2 · Error modeling method and device for prediction context of reversible image watermarking

Abstract

The present disclosure discloses an error modeling method and device for prediction context of reversible image watermarking. A predictor based on omnidirectional context is established; then, the prediction context is self-adaptively error modeled to obtain a self-adaptive error model; and finally, output data from the self-adaptive error model is fed back to the predictor to update and correct the prediction context, so as to correct a prediction value of a current pixel x[i,j]. Since the non-linear correlation between the current pixel and the prediction context thereof, i.e., the non-linear correlation redundancy between pixels can be found by the error modeling of the prediction context of the predictor, the non-linear correlation redundancy between the pixels can be effectively removed. Thus, the embeddable watermarking capacity can be increased.

Claims8

Dependent claims

An error modeling method for prediction context for reversible image watermarking, comprising following steps:

S1:
scanning an original image to obtain a current pixel x[i,j] and adjacent pixels surrounding the current pixel;
S2:
constructing prediction context according to the current pixel x[i,j] and the adjacent pixels surrounding the current pixel, and establishing a predictor based on omnidirectional context;
S3:
self-adaptively error molding the prediction context to obtain a self-adaptive error model;
and
S4:
feeding output data from the self-adaptive error model back to the predictor to update and correct the prediction context, so as to correct a prediction value of the current pixel x[i,j];
wherein the corrected prediction value {dot over (x)} of the current pixel x[i,j] is obtained by:
{dot over (x)}={circumflex over (x)}+ē(d,t)
where, t is the parameter for the quantified predicated context, d is the prediction error of the predictor, ē(d,t) is the error feedback fed back to the predictor by the self-adaptive error model, and {circumflex over (x)} is the prediction value of the current pixel x[i,j] before correction.

9 more elements

A device for storing an error modeling method for prediction context for reversible image watermarking, comprising a control module and a storage medium used for storing control instructions, the control module being configured to read the control instructions in the storage medium and execute the following steps:

Q1:
scanning an original image to obtain a current pixel x[i,j] and adjacent pixels surrounding the current pixel;
Q2:
constructing prediction context according to the current pixel x[i,j] and the adjacent pixels surrounding the current pixel, and establishing a predictor based on omnidirectional context;
Q3:
self-adaptively error molding the prediction context to obtain a self-adaptive error model;
and
Q4:
feeding output data from the self-adaptive error model back to the predictor to update and correct the prediction context, so as to correct a prediction value of the current pixel x[i,j];
wherein the corrected prediction value {dot over (x)} of the current pixel x[i,j] is obtained by:
{dot over (x)}={circumflex over (x)}+ē(d,t)
where, t is the parameter for the quantified predicated context, d is the prediction error of the predictor, ē(d,t) is the error feedback fed back to the predictor by the self-adaptive error model, and {circumflex over (x)} is the prediction value of the current pixel x[i,j] before correction.

9 more elements

Dependencies are inferred from the claim text.

Error modeling method and device for prediction context of reversible image watermarking

Life of this patent

Error modeling method and device for prediction context of reversible image watermarking

Life of this patent

Abstract

Claims8