Evaluation Compressive Sensing Recovery Algorithms in Crypto Steganography System

The main contribution of this paper is using compressive sensing (CS) theory for crypto steganography system to increase both the security and the capacity and preserve the cover image imperceptibility. For CS implementation, the discrete Cosine transform (DCT) as sparse domain and random sensing ma...

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Bibliographic Details
Published in:International journal of image, graphics and signal processing graphics and signal processing, 2016-10, Vol.8 (10), p.53-63
Main Authors: Ranjbar, F. Kafash, Ghofrani, S.
Format: Article
Language:English
Online Access:Get full text
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Summary:The main contribution of this paper is using compressive sensing (CS) theory for crypto steganography system to increase both the security and the capacity and preserve the cover image imperceptibility. For CS implementation, the discrete Cosine transform (DCT) as sparse domain and random sensing matrix as measurement domain are used. We consider 7 MRI images as the secret and 7 gray scale test images as cover. In addition, three sampling rates for CS are used. The performance of seven CS recovery algorithms in terms of image imperceptibility, achieved peak signal to noise ratio (PSNR), and the computation time are compared with other references. We showed that the proposed crypto steganography system based on CS works properly even though the secret image size is greater than the cover image.
ISSN:2074-9074
2074-9082
DOI:10.5815/ijigsp.2016.10.07