Selective image encryption based on pixels of interest and singular value decomposition

In this paper, an efficient yet simple selective encryption technique is proposed based on Saw-Tooth space filling curve, pixels of interest, non-linear chaotic map and singular value decomposition. The core idea of the proposed scheme is to scramble the pixel positions by the means of Saw-Tooth spa...

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Veröffentlicht in:Digital signal processing 2012-07, Vol.22 (4), p.648-663
Hauptverfasser: Bhatnagar, Gaurav, Jonathan Wu, Q.M.
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Jonathan Wu, Q.M.
description In this paper, an efficient yet simple selective encryption technique is proposed based on Saw-Tooth space filling curve, pixels of interest, non-linear chaotic map and singular value decomposition. The core idea of the proposed scheme is to scramble the pixel positions by the means of Saw-Tooth space filling curve followed by the selection of significant pixels using pixels of interest method. Then the diffusion process is done on the significant pixels using a secret image key obtained from non-linear chaotic map and singular value decomposition. Finally, a reliable decryption process is proposed to construct original image from the encrypted image. The analysis and experimental results show that the proposed scheme can achieve various purposes of selective encryption and is computationally secure. ► A new selective encryption technique is proposed using Saw-Tooth SFC, POI and SVD. ► A new space filling curve namely Saw-Tooth SFC is proposed and used. ► A novel criterion based on human perception for selecting pixels (POI) is proposed. ► A secret process is also proposed to convert RGB space to a secret space. ► The feasibility of the proposed technique is proved by different kind of analysis.
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source ScienceDirect Journals (5 years ago - present)
subjects Chaos theory
Construction
Decomposition
Diffusion
Encryption
Non-linear chaotic map
Nonlinearity
Pixels
Pixels of interest
Selective encryption
Singular value decomposition
Space filling curve
title Selective image encryption based on pixels of interest and singular value decomposition
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