Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/4818
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dc.contributor.authorAgrawal, Rohiten_US
dc.contributor.authorAhuja, Kapilen_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-17T15:35:37Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-17T15:35:37Z-
dc.date.issued2021-
dc.identifier.citationAgrawal, R., & Ahuja, K. (2021). CSIS: Compressed sensing-based enhanced-embedding capacity image steganography scheme. IET Image Processing, 15(9), 1909-1925. doi:10.1049/ipr2.12161en_US
dc.identifier.issn1751-9659-
dc.identifier.otherEID(2-s2.0-85102181168)-
dc.identifier.urihttps://doi.org/10.1049/ipr2.12161-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/4818-
dc.description.abstractImage steganography plays a vital role in securing secret data by embedding it in the cover images. Usually, these images are communicated in a compressed format. Existing techniques achieve this but have low embedding capacity. Hence, the goal here is to enhance the embedding capacity while preserving the visual quality of the stego-image. It is also intended to ensure that the scheme is resistant to steganalysis attacks. This paper proposes a compressed sensing image steganography (CSIS) scheme to achieve these goals. In CSIS, the cover image is sparsified block-wise, linear measurements are obtained, and then permissible measurements are selected. Next, the secret data is encrypted, and 2 bits of this encrypted data are embedded into each permissible measurement. For the reconstruction of the stego-image, ADMM and LASSO are used for the resultant optimization problem. Experiments are performed on several standard greyscale images and a colour image. Higher embedding capacity, 1.53 times more compared to the most recent scheme, is achieved. An average of 37.92 dB PSNR value, and average values close to 1 for both the mean SSIM index and the NCC coefficients are obtained, which is considered good. These metrics show that CSIS substantially outperforms existing similar steganography schemes. © 2021 The Authors. IET Image Processing published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technologyen_US
dc.language.isoenen_US
dc.publisherJohn Wiley and Sons Incen_US
dc.sourceIET Image Processingen_US
dc.subjectCompressed sensingen_US
dc.subjectCryptographyen_US
dc.subjectEmbeddingsen_US
dc.subjectImage compressionen_US
dc.subjectSteganographyen_US
dc.subjectEmbedding capacityen_US
dc.subjectEncrypted dataen_US
dc.subjectGrey scale imagesen_US
dc.subjectImage steganographyen_US
dc.subjectLinear measurementsen_US
dc.subjectOptimization problemsen_US
dc.subjectSteganalysis attacksen_US
dc.subjectVisual qualitiesen_US
dc.subjectImage enhancementen_US
dc.titleCSIS: Compressed sensing-based enhanced-embedding capacity image steganography schemeen_US
dc.typeJournal Articleen_US
dc.rights.licenseAll Open Access, Gold, Green-
Appears in Collections:Department of Computer Science and Engineering

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