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The principle of phase compensation on the metasurfaces is applied to realize the cloaking function, which provides a new idea for the further development of invisibility technology. However, the uppermost layer of the metasurface carpet cloak previously studied is mostly a metal structure with ohmic loss and low coupling efficiency. In practical applications, these ordinary invisibility cloaks are easy to be corroded, and does not endure high temperature, and only has the function of invisibility under the action of the same polarization. Here, we propose to use the unit structure of high-refractive-index dielectric silicon resonators to construct the invisibility cloak, which can better reduce loss, improve reflection efficiency, and can be better applied to practical applications. A unique cross polarization stealth device with the broadband cloaking effect is designed to effectively resist cross polarization detectors. Objects of arbitrary shape can be hidden under the triangular carpet stealth device designed to achieve the purpose that the detector cannot detect, so as to achieve stealth function. The working wavelength of the cloak proposed is at 1550nm, achieving the effect of cross polarization invisibility in the communication band. [ABSTRACT FROM AUTHOR]

In order to reduce the ohmic loss, we propose all dielectric reflection metasurface in terahertz band. The unit structure can be encoded to construct all dielectric reflection encoding metasurfaces. The all dielectric coded metasurfaces consist of the physical coded particles with the coded digits. Since it is impossible for us to design and prepare coded particles of infinitely small size, the traditional coded metasurfaces only control the limited scattering beam directions especially for small deflection angles, and cannot achieve continuous control of scattering angles. This severely limits the wide application of coded metasurfaces. In order to achieve multi-directions and large angle scattering, we introduce the Fourier convolution principle from digital signal processing on all dielectric reflection encoding metasurfaces. Through the addition and subtraction operations of all dielectric encoding metasurface sequences, the freely manipulation of scattering beams can be achieved, especially for larger deflection angles. More importantly, compared with the traditional gradient phase coded metasurfaces, the mixed coded metasurfaces by addition and subtraction operations of encoding sequences can greatly improve the scattering cross section. [ABSTRACT FROM AUTHOR]

With the introduction of artificial intelligence (AI), current deep learning-driven change detection methods generally regard changes as a type of specific land cover information and try to detect them simply by using existing semantic labeling models. In practice, the changes that occur on different land cover categories may appear completely different for remote sensing images, making it difficult to detect multiple categories of changes with an end-to-end model. In addition, training such networks requires a large amount of prelabeled references, which are labor-intensive and time-consuming. Motivated by this observation, we integrate dual learning algorithm and disentangled representation theory to develop a novel approach, named content-invariant dual learning (CiDL), for either supervised or unsupervised change detection in remote sensing images. In our framework, two opposite Y-shaped networks, each of which consists of two encoders and one decoder, are introduced to translate bitemporal images from their original domains to each others, where their intrinsic content features are retained, while their style features are consistent. By training our hybrid framework, even without references, this method learns a category-wise cross-domain translation to suppress the discrepancies in paired unchanged regions, and meanwhile highlight those in paired changed regions. The experimental results on two typical change detection data sets and the comparison with other state-of-the-art deep learning-driven methods verify the effectiveness and competitiveness of our proposed CiDL. [ABSTRACT FROM AUTHOR]

Regarding landslide inventory mapping (LIM) as a task similar to change detection, current methods for LIM using bi-temporal optical remote sensing images are generally derived from change detection methods. In practice, not all changed regions belong to landslides, e.g., new roads, canals, and vegetation. Therefore, an ideal strategy is supposed to present two steps: discriminating changed and unchanged regions, and detecting landslides apart from other changed regions. Owing to the complexity and uncertainty of landslides, it is difficult to simultaneously separate landslides with unchanged and other changed regions by a single model. Addressing this problem, in this letter, we apply a generative adversarial network (GAN) in a Siamese neural network, and then propose a GAN-based Siamese framework (GSF) for LIM. The GSF comprises two cascaded modules, namely, domain adaptation and landslide detection. The former module aims to make a cross-domain mapping between prelandslide and postlandslide images with adversarial learning, then translate paired images into the same domain to suppress the domain discrepancies of bi-temporal remote sensing images. Meanwhile, the latter module aims to perform pixel-level landslide detection with a Siamese model. By training this cascaded framework, our method learns to produce landslide inventory maps without any preprocessing or postprocessing. Extensive experiments and comparison with other state-of-the-art methods verify the efficiency and superiority of our method. [ABSTRACT FROM AUTHOR]

A full-range line-field Fourier-domain optical coherence tomography (LF-FDOCT) system with an accuracy at nanoscale was proposed for high-accuracy measurements of optical lens surface profile. The LF surface curve information of optical lens could be obtained in one measurement which does not need point-by-point scanning used in the traditional 1-D FDOCT system. The measurement accuracy of surface profile curve could be improved from micrometer scale to nanoscale by applying spectral center correction method (SCCM) to the complex spectral interferogram. The corrected five phase-shifting (CFPS) method was employed to eliminate the complex-conjugate artifacts and the polychromatic error. The numerical simulation and experiment results demonstrated that the CFPS method had a better complex-conjugate suppression performance than other phase-shifting methods. Optical lens (e.g., cylindrical lens and spherical lens) was measured by the homemade LF-FDOCT system. After the analysis of the surface profile, the radius and the optical focal length of the measured lens were precisely obtained in a noncontact and nondestructive way. Therefore, the developed LF-FDOCT system has provided a new tool for high-accuracy measurements of optical lens surface profile and its parameters. [ABSTRACT FROM AUTHOR]

A full-range line-field Fourier-domain optical coherence tomography (LF-FDOCT) system with an accuracy at nanoscale was proposed for high-accuracy measurements of optical lens surface profile. The LF surface curve information of optical lens could be obtained in one measurement which does not need point-by-point scanning used in the traditional 1-D FDOCT system. The measurement accuracy of surface profile curve could be improved from micrometer scale to nanoscale by applying spectral center correction method (SCCM) to the complex spectral interferogram. The corrected five phase-shifting (CFPS) method was employed to eliminate the complex-conjugate artifacts and the polychromatic error. The numerical simulation and experiment results demonstrated that the CFPS method had a better complex-conjugate suppression performance than other phase-shifting methods. Optical lens (e.g., cylindrical lens and spherical lens) was measured by the homemade LF-FDOCT system. After the analysis of the surface profile, the radius and the optical focal length of the measured lens were precisely obtained in a noncontact and nondestructive way. Therefore, the developed LF-FDOCT system has provided a new tool for high-accuracy measurements of optical lens surface profile and its parameters. [ABSTRACT FROM AUTHOR]