Please use this identifier to cite or link to this item:
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.
Appears in Collections:1. Journal Articles

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.