Quick image scrambling method based on local equilibrium ternary tree theory

Abstract

The invention discloses a quick image scrambling method based on a local equilibrium ternary tree theory, wherein the scrambling method comprises the following steps: a first element of an original image is used as a root node of a ternary tree, three elements closely neighbored to the first element are used as left, middle and right subnodes of the root node; three elements closely neighbored to the middle node are used as left, middle and right subnodes of the node; one element closely neighbored to the left node is used as the subnode of the node, one element closely neighbored to the right node is used as the subnode of the node; by parity of reasoning, the entire image matdix is used as a local equilibrium ternary tree. An ergodic process comprises the following steps: the root node is traversed; the traverse is carried out according to the level of the tree, every layer is sequentially traversed according to the middle, left and right nodes. The traversed elements are stored in a one-dimensional numerical group; the one-dimensional numerical group is transformed to the size of the original image to finish the positive scrambling of the image. The method can quickly reach an ideal scrambling effect, and the scrambling is stable, the image recovered after scrambling is free from loss; the method has relatively strong ability in shear resistance, compression, wave filtering and noise attack.

Description

technical field [0001] The invention relates to a fast image scrambling method of a locally balanced triple tree, is an information hiding preprocessing method and an image encryption means, and belongs to the field of digital image processing. Background technique [0002] With the wide application of images in all aspects of social life, the security requirements for image transmission are getting higher and higher. Information hiding and camouflage technology are the main means to solve its security, and digital image scrambling technology is an effective information Concealing the preprocessing method and image encryption means, the scrambling technology has been greatly developed. The principle is to transform a given image in the spatial domain or frequency domain according to certain transformation rules, so that the transformed image looks chaotic and meaningless, so as to achieve the purpose of image information hiding. Currently existing scrambling techniques such...

AI Technical Summary

Problems solved by technology

Currently existing scrambling techniques such as Arnold transform, Hilbert curve, Fibonacci, and P-Fibonacci transform mainly involve modulo calculations, which require a relatively large amount of calculation, time-consuming scrambling, unsatisfactory scrambling speed, and relatively low efficiency; and They are mainly used for square matrix images, and the applicability of scrambling is not good; the scrambling method based on sampling technology has a sampling period, and the sampling period is short, but the scrambling effect is not ideal, and the scrambling image can see the original image. some information

[0003] At present, there are many scrambling techniques, but there are many problems, and there are few methods based on the tree structure in the data structure, so it is quite challenging to study a good tree-based scrambling method.

[0004] Moreover, most of the existing scrambling methods use matrix transformation, modulo operation, curve scanning and other methods. These methods are time-consuming, but the traversal of the tree structure is simple and fast, and has good applicability.

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