Encrypted image reversible information hiding method based on quadtree dynamic block segmentation

Abstract

The invention relates to an encrypted image reversible information hiding method based on quadtree dynamic block segmentation. The method comprises the following steps: 1) reserving a space before image encryption by using a quadtree dynamic block segmentation method; 2) carrying out scrambling and encryption on the image by adopting a chaotic stream password; (3) carrying out information hiding on a scrambled and encrypted image, (4) extracting hidden information, 4(5) generating a decryption-password-carrying image for the image from which the hidden information is extracted, replacing a bit, and carrying out image restoration. compared with the prior art, the method has the advantages of simplicity in implementation, high safety, high steganography capacity and the like.

Description

technical field The invention relates to the technical field of digital image processing, in particular to a method for reversible information hiding of encrypted images based on quadtree dynamic block segmentation. Background technique In recent years, with the development of network, cloud computing and other technologies, traditional image encryption and plaintext information hiding methods have gradually been unable to meet people's strong demand for information security. Encryption technology and information hiding technology do not conflict with the security protection of carrier transmission, but complement each other, so they can be combined to achieve double protection of carrier transmission. Reversible information hiding methods for encrypted images can be mainly divided into two categories, namely reserving space before encryption (RRBE, reserving room before encryption) and vacating room after encryption (VARE, vacating room after encryption). RRBE reserves spa...

AI Technical Summary

Problems solved by technology

However, through the research of existing methods, it is found that most of the current methods have small embedding amount and high computational complexity, and cannot separate the texture area and smooth area of ​​the image well, and cannot make full use of the natural image correlation, which leads to algorithm embedding. small amount

In addition, high computational complexity and poor encryption security are also common flaws of existing methods

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