Redundant Image Representations in Security Applications

To be efficient, data protection algorithms should generally exploit the properties of the media information in the transform domain. In this paper, we will advocate the use of non-linear image approximations using highly redundant dictionaries, for security algorithms. We show that a flexible image representation based on a multidimensional and geometry-based coding scheme, has precious attributes for security information embedding. Redundant expansions provide very good approximation properties, as well as an increased resiliency to coding noise, and a simple stream structure enables easy manipulations. This paper describes simple examples of image scrambling and watermarking applications, based on a Matching Pursuit image coder. It illustrates the very interesting potential of redundant decompositions for data protection and security applications

Sparsity and `Something Else': An Approach to Encrypted Image Folding

A property of sparse representations in relation to their capacity for information storage is discussed. It is shown that this feature can be used for an application that we term Encrypted Image Folding. The proposed procedure is realizable through any suitable transformation. In particular, in this paper we illustrate the approach by recourse to the Discrete Cosine Transform and a combination of redundant Cosine and Dirac dictionaries. The main advantage of the proposed technique is that both storage and encryption can be achieved simultaneously using simple processing steps.Comment: Revised manuscript- Software for implementing the Encrypted Image Folding proposed in this paper is available on http://www.nonlinear-approx.info