Visible to the public Biblio

Filters: Keyword is optical information processing  [Clear All Filters]
Uto, K., Mura, M. D., Chanussot, J..  2018.  Spatial Resolution Enhancement of Optical Images Based on Tensor Decomposition. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. :8058-8061.

There is an inevitable trade-off between spatial and spectral resolutions in optical remote sensing images. A number of data fusion techniques of multimodal images with different spatial and spectral characteristics have been developed to generate optical images with both spatial and spectral high resolution. Although some of the techniques take the spectral and spatial blurring process into account, there is no method that attempts to retrieve an optical image with both spatial and spectral high resolution, a spectral blurring filter and a spectral response simultaneously. In this paper, we propose a new framework of spatial resolution enhancement by a fusion of multiple optical images with different characteristics based on tensor decomposition. An optical image with both spatial and spectral high resolution, together with a spatial blurring filter and a spectral response, is generated via canonical polyadic (CP) decomposition of a set of tensors. Experimental results featured that relatively reasonable results were obtained by regularization based on nonnegativity and coupling.

Birch, G. C., Woo, B. L., LaCasse, C. F., Stubbs, J. J., Dagel, A. L..  2017.  Computational optical physical unclonable functions. 2017 International Carnahan Conference on Security Technology (ICCST). :1–6.

Physical unclonable functions (PUFs) are devices which are easily probed but difficult to predict. Optical PUFs have been discussed within the literature, with traditional optical PUFs typically using spatial light modulators, coherent illumination, and scattering volumes; however, these systems can be large, expensive, and difficult to maintain alignment in practical conditions. We propose and demonstrate a new kind of optical PUF based on computational imaging and compressive sensing to address these challenges with traditional optical PUFs. This work describes the design, simulation, and prototyping of this computational optical PUF (COPUF) that utilizes incoherent polychromatic illumination passing through an additively manufactured refracting optical polymer element. We demonstrate the ability to pass information through a COPUF using a variety of sampling methods, including the use of compressive sensing. The sensitivity of the COPUF system is also explored. We explore non-traditional PUF configurations enabled by the COPUF architecture. The double COPUF system, which employees two serially connected COPUFs, is proposed and analyzed as a means to authenticate and communicate between two entities that have previously agreed to communicate. This configuration enables estimation of a message inversion key without the calculation of individual COPUF inversion keys at any point in the PUF life cycle. Our results show that it is possible to construct inexpensive optical PUFs using computational imaging. This could lead to new uses of PUFs in places where electrical PUFs cannot be utilized effectively, as low cost tags and seals, and potentially as authenticating and communicating devices.

Li, W., Ji, J., Zhang, G., Zhang, W..  2016.  Cross-layer security based on optical CDMA and algorithmic cryptography. 2016 IEEE Optoelectronics Global Conference (OGC). :1–2.

In this paper, we introduce an optical network with cross-layer security, which can enhance security performance. In the transmitter, the user's data is encrypted at first. After that, based on optical encoding, physical layer encryption is implemented. In the receiver, after the corresponding optical decoding process, decryption algorithm is used to restore user's data. In this paper, the security performance has been evaluated quantitatively.