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A JPEG lossless compression image hide writing method based on predictive coding

A lossless compression and predictive coding technology, which is applied in image communication, television, electrical components, etc., can solve the problems of large embedded data, image statistical characteristics, poor ciphertext image quality, weak anti-attack ability, etc., and achieve high algorithm security , strong practicability, and less damage to image statistics

Inactive Publication Date: 2007-11-28
SUN YAT SEN UNIV
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Problems solved by technology

[0007] The invention overcomes the disadvantages of poor ciphertext image quality and weak anti-attack ability of the existing steganography algorithm based on predictive coding, and proposes a steganographic algorithm based on a large amount of embedded data, good ciphertext image quality, and little damage to image statistical features. Predictive Coding JPEG Lossless Compression Image Steganography Method

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  • A JPEG lossless compression image hide writing method based on predictive coding
  • A JPEG lossless compression image hide writing method based on predictive coding
  • A JPEG lossless compression image hide writing method based on predictive coding

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Embodiment Construction

[0038] The present invention will be further described below in conjunction with the embodiments and accompanying drawings.

[0039] As shown in Figures 1 to 6, the embedding process of the inventive method is as follows:

[0040] First, select the secret message to be delivered, which can be any file such as text, image, audio, etc., and convert it into a binary sequence. In this example, the 95×90 grayscale image shown in Figure 6(b) is used as the secret information, and the file size is 1142 bytes. It is encrypted and converted into a binary sequence of 01000010...0, a total of 9136 bits.

[0041] Secondly, choose a carrier image with JPEG lossless compression. The size of the image can be used as a reference for the length of the secret information, that is, an appropriate embedding rate h should be selected. In this example, the 512×512×8bits Lena image as shown in Figure 7(a) is used as the carrier image, the total file size is 169140 bytes, and the gray value is shown...

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Abstract

This invention discloses a hidden-writing method for JPEG lossless compressed images based on forecast coding, when inserting data in a JPFG lossless compressed image, it first of all carries Huffman decoding to get a forecast error, then inserts secret data in the forecast error and finally carries out Huffman coding to the modified forecast error to generate cryptograph image of the JPEG lossless coding, which utilizes modular arithmetic when inserting, which not only reduces alteration of data insertion to carrier images to keep a rather high image quality but also stores the inserted data either in the lossless compressed JPRG code streams or in the compressed cryptograph images.

Description

technical field [0001] The invention belongs to the field of multimedia signal processing, and in particular relates to a steganographic method for JPEG lossless compressed images based on predictive coding. Background technique [0002] With the continuous progress of multimedia signal processing technology, information hiding is being applied to the field of information security more and more. There are mainly two methods for digital image steganography, namely, spatial domain and transform domain methods. The most typical steganographic algorithm in the airspace is the LSB substitution method, which is simple and easy to implement, but it has already been broken. The steganography algorithm as a transform domain can be divided into three types: DFT, DCT and DWT, most of which are for DCT-based JPEG lossy compressed images, representative algorithms are: J-Steg, F5, OutGuess, Model-Based, etc. , but these algorithms have been broken one after another. [0003] For the s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N7/26H04N7/30H04N7/32H04N7/50H04N19/467
Inventor 方艳梅刘永清李斌黄继武
Owner SUN YAT SEN UNIV
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