Image compression secure coding method based on multidirectional sparse representation

Abstract

The invention discloses an image compression secure coding method based on multidirectional sparse representation, comprising the following steps of: performing discrete dual-tree wavelet transform on an image and then performing directional filtering on each obtained high-frequency sub-band to obtain fine image directional sparse representation; performing rarefaction process on an obtained directional sub-band coefficient by using a noise shaping technology; interleaving the coefficients of each layer to ensure that the sub-band coefficients of neighbor layers have a parent child relation, and then performing quantitative coding on the coefficients by using SPIHT (Set Partitioning in Hierarchical Trees); and finally encrypting the coefficient symbols in a code stream in an XOR (Exclusive OR) manner and encrypting other partial code streams by using random arithmetic coding. As the code stream obtained by coding is encrypted by using the random arithmetic coding, the encryption efficiency is high, the effect is good, the security is high and no influence is brought to the image compression performance. The high-frequency components of the image are decomposed by using a directional filter, and therefore the directional representation is more flexible, sparser image representation is obtained, the image coding compression process is favored and the decoded image has better objective quality and subjective effect.

Description

technical field [0001] The invention relates to a secure encoding method based on image compression, in particular to an image compression secure encoding method based on multi-directional sparse representation of random arithmetic coding. Background technique [0002] With the rapid development of multimedia such as networks and images, multimedia communication such as images has gradually become an important means of information exchange between people. The current network is an open system, so before transmitting important images, images need to be encrypted to ensure security. The traditional encryption technology encrypts it as an ordinary data stream without considering the characteristics of multimedia data, so it has certain limitations. For example, the data volume of an image is generally relatively large, and the amount of calculation required for encryption is relatively large, resulting in the problem of low encryption efficiency. In addition, the data size of...

AI Technical Summary

Problems solved by technology

However, DWT has two major drawbacks: (1) lack of translation invariance, that is, a small translation of the input signal can lead to large changes in DWT coefficients; (2) lack of direction selectivity, that is, for non-horizontal or non-vertical singular Features are difficult to express efficiently

However, this transformation needs to find the optimal decomposition structure, so the computational complexity is relatively high

[0004] According to the image compression process, image encryption is divided into three categories: (1) Encrypt the image before compression encoding. The statistics between them are destroyed, and compression processing cannot be performed, which is not conducive to the storage and transmission of images

(2) The image is compressed and encoded before being encrypted. The data volume of the image is relatively large, and the computational complexity of traditional encryption methods such as AES is relatively high, which is not conducive to real-time processing.

However, this will destroy the law of transform domain coefficients, which is not conducive to the subsequent compression coding of images.

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