Research On Image Reversible Data Hiding Algorithm Based On Pixel Value Ordering

In the past two decades,Data hiding has attracted widespread attention in the research community.Reversible Data hiding has become a very active research field in the field of information hiding.Through this technology,the secret information is embedded in the carrier medium,and the secret-carrying medium can be obtained,and then the embedded secret information can be extracted from the marked medium.However,for most Data hiding methods,the covering medium loses part of the information during the secret information embedding operation,so the information cannot be retrieved and restored to the original carrier.In some sensitive situations,the original carrier needs to be obtained.To solve this problem,reversible information hiding,called lossless or reversible information hiding,is proposed to recover embedded secret information and carrier media losslessly.This technology is widely used in many fields,including image authentication,medical image processing,and digital copyright protection.Reversible information hiding can not only extract secret information,but also restore the original image.It plays an important role in sensitive fields such as military,medical and judicial identification.The reversible information hiding in the plaintext domain can not only realize the lossless recovery of the original carrier,but also extract the secret information accurately and accurately.It has a wide range of applications in the field of information security.This paper is mainly based on the research of the reversible Data hiding algorithm for plaintext images.The main research results are as follows:1.A reversible image Data hiding algorithm based on local pixel value order and prediction difference is proposed.The previous difference expansion method is improved,and the reversible Data hiding scheme proposed by Peng et al.to improve pixel value order is expanded.In the method of Peng et al.,the maximum and minimum values ??of pixel blocks are predicted and modified to embed information.After the information is embedded,the order of the pixel values ??of each block remains unchanged,and reversibility is guaranteed.In this work of this paper,the method considers the combined difference expansion method in the block to improve the experiment.In this scheme,the maximum value,minimum value of the block and the pixel embedding outside the sort sequence in the block are the new histogram modification strategy.The method is to predefine the pixel position to improve the secret information embedding capacity and the distortion of the carrier image.In this way,the maximum value,minimum value,and pixels outside the sorted sequence in the block can be used to embed secret information,and this histogram modification method has not been used in the previous work.This can make better use of image redundancy and achieve better embedding performance.A large number of experiments have verified that the effectiveness of this method is better than some other most advanced schemes.2.A reversible information hiding algorithm based on pixel value order of local partial blocks is proposed.The original image is overlapped and divided into blocks,the fixed position pixel in the block is used as the reference pixel,the pixel outside the pixel sequence in the block is selected as the pixel embedded with the secret information,and then the maximum or minimum value is selected and the difference expansion method is used to calculate the fixed pixel and the undefined pixel.The difference of the pixel prediction of the embedded secret information is used to embed the secret information.This method sorts the fixed pixels in the block in ascending order to obtain the carrier image.For secret information extraction and image restoration,the reverse step of this method is used.The carrier image is first overlapped and divided into blocks,and then the pixel value sorting method is used to extract the secret information from the pixels embedded by the pixel value sorting method and restore the original image,and then use The extraction method of prediction difference extracts the secret information in another pixel and restores the image.