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https://idr.l4.nitk.ac.in/jspui/handle/123456789/16370
Title: | A secure visual secret sharing (VSS) scheme with CNN-based image enhancement for underwater images |
Authors: | Mhala N.C. Pais A.R. |
Issue Date: | 2020 |
Citation: | Visual Computer , Vol. , , p. - |
Abstract: | Nowadays, underwater images are being used to identify various important resources like objects, minerals, and valuable metals. Due to the wide availability of the Internet, we can transmit underwater images over a network. As underwater images contain important information, there is a need to transmit them securely over a network. Visual secret sharing (VSS) scheme is a cryptographic technique, which is used to transmit visual information over insecure networks. Recently proposed randomized VSS (RVSS) scheme recovers secret image (SI) with a self-similarity index (SSIM) of 60–80%. But, RVSS is suitable for general images, whereas underwater images are more complex than general images. In this paper, we propose a VSS scheme using super-resolution for sharing underwater images. Additionally, we have removed blocking artifacts from the reconstructed SI using convolution neural network (CNN)-based architecture. The proposed CNN-based architecture uses a residue image as a cue to improve the visual quality of the SI. The experimental results show that the proposed VSS scheme can reconstruct SI with almost 86–99% SSIM. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature. |
URI: | https://doi.org/10.1007/s00371-020-01972-9 http://idr.nitk.ac.in/jspui/handle/123456789/16370 |
Appears in Collections: | 1. Journal Articles |
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