Image watermarking method and system fusing intra-block and inter-block texture rule features of image

Abstract

The invention discloses an image watermarking method and system fusing intra-block and inter-block texture rule features of an image, and the method comprises the steps: carrying out the DCT of a to-be-embedded image after partitioning, extracting a DCT coefficient, and forming a to-be-embedded vector; obtaining a texture regularity modulation factor based on the texture rule characteristics in the image intra-block and image inter-block, constructing a JND model based on the texture regularity modulation factor, and calculating a JND basic threshold to obtain a perception relaxation vector; mapping the vector to be embedded and the perceptual relaxation vector to a given projection vector, respectively obtaining a projection vector to be embedded and a perceptual relaxation projection vector, and obtaining a quantization step length through the perceptual relaxation projection vector and the embedding intensity; and embedding the watermark into the projection vector to be embedded according to the quantization step length, and performing IDCT on the DCT coefficient to obtain an image embedded with the watermark. The intra-block texture rule characteristics and the inter-block texture rule characteristics are respectively measured, and the robustness of the watermarking algorithm is improved while the visual quality of the image is ensured.

Description

technical field [0001] The disclosure relates to the technical field of digital image content security protection, in particular to an image watermarking method and system for fusing texture regular features within and between image blocks. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] Nowadays, science and technology are changing with each passing day, and the rapid development of multimedia technology and computer network technology has promoted the increasing popularity of network digital multimedia technology and its applications. The commercial use of 5G networks has further promoted the rapid dissemination of digital information, making it easier and faster for people to download and upload digital multimedia information. With the popularity of photo-sharing platforms and apps such as Lofter, Pixel Bee, Tuchong, and poco, more an...

AI Technical Summary

Problems solved by technology

[0007] The Watson vision model does not represent human vision well and is not robust to common FGA attacks

The visual JND model designed in the digital watermarking algorithm based on structural regularity proposed by Xu et al. only considers the structural regularity characteristics in the image block, and cannot well reflect the perceptual characteristics of the human visual system.

In the quantitative watermarking algorithm system, there are two limitations when the existing JND model is used to calculate visual redundant information: First, the traditional visual JND model cannot meet the robustness requirements of the watermarking algorithm, which is manifested in: the embedding of the watermark changes The image pixel information also causes the inconsistency between the visual JND models calculated at the watermark embedding end and the extraction end. Therefore, in the absence of attacks, the watermark information extracted blindly will still have extraction errors; the second is that the JND model targets The evaluation of the impact of image texture regularity on visual redundancy is not accurate enough, that is, only the texture regular features in the image block are considered in the calculation of the model, and the mutual influence between image blocks is not considered, ignoring the overall texture of the image The impact of regular features on visual redundancy assessment and thus not a good estimate of true visual perceptual redundancy

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