Over the years extensive studies have been carried out to apply coherent optics methods in real-time communications and image transmission. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. However, the transmitted data can be intercepted by nonauthorized people. This explains why considerable effort is being devoted at the current time to data encryption and secure transmission. In addition, only a small part of the overall information is really useful for many applications. Consequently, applications can tolerate information compression that requires important processing when the transmission bit rate is taken into account. To enable efficient and secure information exchange, it is often necessary to reduce the amount of transmitted information. In this context, much work has been undertaken using the principle of coherent optics filtering for selecting relevant information and encrypting it. Compression and encryption operations are often carried out separately, although they are strongly related and can influence each other. Optical processing methodologies, based on filtering, are described that are applicable to transmission and/or data storage. Finally, the advantages and limitations of a set of optical compression and encryption methods are discussed.

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International audienceApproximation of discrete cosine transform (DCT) is useful for reducing its computational complexity without significant impact on its coding performance. Most of the existing algorithms for approximation of the DCT target only the DCT of small transform lengths, and some of them are non-orthogonal. This paper presents a generalized recursive algorithm to obtain orthogonal approximation of DCT where an approximate DCT of length N could be derived from a pair of DCTs of length (N/2) at the cost of N additions for input preprocessing. We perform recursive sparse matrix decomposition and make use of the symmetries of DCT basis vectors for deriving the proposed approximation algorithm. Proposed algorithm is highly scalable for hardware as well as software implementation of DCT of higher lengths, and it can make use of the existing approximation of 8-point DCT to obtain approximate DCT of any power of two length, N > 8. We demonstrate that the proposed approximation of DCT provides comparable or better image and video compression performance than the existing approximation methods. It is shown that proposed algorithm involves lower arithmetic complexity compared with the other existing approximation algorithms. We have presented a fully scalable reconfigurable parallel architecture for the computation of approximate DCT based on the proposed algorithm. One uniquely interesting feature of the proposed design is that it could be configured for the computation of a 32-point DCT or for parallel computation of two 16-point DCTs or four 8-point DCTs with a marginal control overhead. The proposed architecture is found to offer many advantages in terms of hardware complexity, regularity and modularity. Experimental results obtained from FPGA implementation show the advantage of the proposed method

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Here we present a new approach of multiplexing and simultaneous encoding of target images. Our approach can enhance the encryption level of a classical double random phase (DRP) encryption system by adding a supplementary security layer. The new approach can be divided into two security layers. The first layer is called the multiplexing level, which consists in using iterative Fourier transformations along with several encryption key images. These latter can be a set of biometric images. At the second layer, we use a classical DRP system. The two layers enable us to encode several target images (multi-encryption) and to reduce, at the same time, the requested decoded information (transmitted or storage information).

Underwater target detection is investigated by combining active polarization imaging and optical correlation-based approaches. Experiments were conducted in a glass tank filled with tap water with diluted milk or seawater and containing targets of arbitrary polarimetric responses. We found that target estimation obtained by imaging with two orthogonal polarization states always improves detection performances when correlation is used as detection criterion. This experimentally study illustrates the potential of polarization imaging for underwater target detection and opens interesting perspectives for the development of underwater imaging systems.