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Some methods developed in reversible data hiding (RDH) make use of prediction for data embedding for original pixel estimation. Predicators may also be exploited in RDH in encrypted image (RDHEI); this has become a research interest in recent years because of the development of cloud computing and a need for content owner privacy. This paper presents a high-capacity reversible data hiding in encrypted image (RDHEI) that employs local difference predictor. In this algorithm, an image is divided into non-overlapping blocks. In each block, the central pixel of the block is considered as the leader pixel and others as follower ones. The prediction errors between the intensity of the follower pixels and leader one are calculated using local difference predictor and analyzed to determine a label for block embedding capacity. This label indicates the amount of data that can be embedded in a block after encryption. Using this pre-processing for all blocks, we vacate rooms before the encryption of the original image to achieve high embedding capacity. Also, using these labels, embedded data is extracted and the original image is losslessly reconstructed at the decoding phase. Comparing to existent RDHEI algorithms, not only embedding capacity is increased by the proposed algorithm, but also a perfect reconstruction of the original image is realized by content owner without having data hider key. Experimental results confirm that the proposed algorithm outperforms state of the art RDHEI methods. [ABSTRACT FROM AUTHOR]

This paper presents a linear synthetic focusing method (SFM) in order to mitigate the drawbacks of the classical multiple signal classification (MUSIC) algorithm for microwave imaging (MI). The determination of noise subspace dimension for MUSIC algorithm is a challenge when imaging an extended target. That is because an extended target comprises many point scatterers and a practical MI system provides an incomplete multistatic response (IMSR) matrix. The SFM obtains a focused multistatic response matrix for each location in the imaging region, which contains, mostly, the scattered field of a point scatterer at that location. In this way, the signal subspace is reduced to the one for a point scatterer, whose singular values are well-separated from those of the noise subspace. The proposed SFM is applied to the breast cancer detection using synthetic data. It is also applied to the experimental data given by Institute Fresnel to test the SFM for scenarios other than biomedical uses. It is shown that the SFM provides superior results over the classical MUSIC algorithm, especially for extended targets and IMSR matrices. [ABSTRACT FROM AUTHOR]

This letter focuses on the modification of a unit cell of a metamaterial absorber to decrease its operational frequency. By decreasing the operational frequency, we can increase capability of the absorber for practical applications and decrease sensitivity of the structure response to the curvature. The structure has been implemented by the array of the unit cell on the FR4 substrate in the front of a conductive plate. Both the simulated and experimental results indicate the structure provides 20% decrease in the minimum operation frequency with respect to the reference structure. Also, the operating frequency range of the structure with absorptivity more than 90% is 1.35–3.5 GHz, i.e., 88% fractional bandwidth. The structure has appropriate response under oblique incident angle from 0° to 40°. [ABSTRACT FROM AUTHOR]

Multiple signal classification (MUSIC) method uses the multi-static response matrix (MSR) to locate small inclusions in a microwave imaging (MI) system. The MSR cannot accommodate all available data in an actual MI system because practical restrictions make some receivers be inactive for every active transmitter. The current work presents a method for completing the MSR acquired in practical systems. Using the least squares method, the complete MSR matrix is formed by the estimation of its unknown elements, associated to the signal at inactive receivers. The estimation algorithm employs the signal of other active receivers to obtain inactive receiver signals. In this way, all available data contributes in imaging, which improves the localization performance. The merits of our proposal are demonstrated using the Institut Fresnel experimental data sets as well as various realistic synthetic data. [ABSTRACT FROM PUBLISHER]

Deals with a study that proposed an inverse scattering method for the reconstruction of the permittivity and conductivity profiles of a multilayered medium and for that of the impedance profile of a nonuniform transmission line. Formulation of the forward problem; Inverse scattering method; Reconstruction examples; Conclusion.

Presents a study which developed a calibration technique for free-space measurement of the permittivity and conductivity from ground penetrating radar. Antenna-medium coupling of the technique; Principles of operation; Discussion on the results of the study; Conclusion.