Visual fidelity without sacrificing capacity: an adaptive Laplacian pyramid approach to information hiding

Tamer Rabie; Mohammed Baziyad

doi:10.1117/1.JEI.26.6.063001

1 November 2017 Visual fidelity without sacrificing capacity: an adaptive Laplacian pyramid approach to information hiding

Tamer Rabie, Mohammed Baziyad

Author Affiliations +

Journal of Electronic Imaging, Vol. 26, Issue 6, 063001 (November 2017). https://doi.org/10.1117/1.JEI.26.6.063001

Abstract

This paper investigates the improvements in hiding capacity and perceptibility of image-based steganography using a hiding scheme which utilizes a multiscale Laplacian pyramid of the cover image and the discrete cosine transform (DCT). The proposed methodology allows for an enhanced visual quality of the resulting stego image, while allowing for very high embedding payload capacities, which improves security by reducing an eavesdropper’s ability to detect and successively extract or change the hidden information. The basic idea is to hide the secret data in the DCT of the lowest level of the Laplacian pyramid of the cover image. This scheme employs a curve-fitting adaptive region approach in the DCT domain for enhanced visual fidelity as well as very high capacities as compared to competing methods. This paper also compares the embedding capacities of various steganography schemes that have been recently published in the literature. Experimental results confirm that the proposed hiding scheme can maintain consistently high stego image quality, in comparison to other spatial and frequency-domain schemes, when hiding at extremely high payload capacities.

Citation Download Citation

Tamer Rabie and Mohammed Baziyad "Visual fidelity without sacrificing capacity: an adaptive Laplacian pyramid approach to information hiding," Journal of Electronic Imaging 26(6), 063001 (1 November 2017). https://doi.org/10.1117/1.JEI.26.6.063001

Received: 19 January 2017; Accepted: 5 October 2017; Published: 1 November 2017

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available