Non-orthogonal polarization multiplexed metasurfaces for tri-channel polychromatic image displays and information encryption

Interference usually occurs between two non-orthogonally polarized light beams. Hence, metasurface enabled polarization multiplexing is generally conducted under two orthogonal polarization states to realize independent intensity and/or phase modulations. Herein, we show that polarization multiplexed metasurfaces can work under three non-orthogonal polarization states to realize tri-channel image displays with independent information encoding. Specifically, enabled by orientation degeneracy, each nanostructure of the metasurface operates with triple-manipulations of light, i.e., two channels for independent intensity manipulation under π/4 and 3π/8 linearly polarized (LP) light, respectively, and one channel for phase manipulation without polarization control. We experimentally demonstrate this concept by recording one continuous-brightness polychromatic image and one binary-brightness polychromatic image right at the metasurface plane, while a continuous-brightness polychromatic image is reconstructed in the far field, corresponding to three independent channels, respectively. More interestingly, in another design strategy with separated image encoding of two wavelengths, up to six independent image-display channels can be established and information delivery becomes safer by utilizing encryption algorithms. With the features of high information capacity and high security, the proposed meta-devices can empower advanced research and applications in multi-channel image displays, orbital angular momentum multiplexing communication, information encryption, anti-counterfeiting, multifunctional integrated nano-optoelectronics, etc.

At the source of integrated interactions across channels

PurposeThis research studies what full channel integration means for customers, how channels should be combined so that this integration is perceived by customers and whether a retailer under study can act on the same channel attributes regardless of the type of customer.Design/methodology/approachThe research design uses an online survey of a full sample of 1,015 multichannel buyers, extracted from the behavioral databases of a French specialized retailer. This full sample is segmented into four sub-samples. The data are treated with backward multiple linear regressions.FindingsBased on research in marketing and psychology, this study conceptually demonstrates that integrated interactions perceived by consumers are the outcome of a judgment of congruence that seek to build relationships between them in order to combine them better. Testing three hypotheses, the empirical study shows that channel integration is a psychological process: cumulative (individuals incorporate the information provided by the different channels rather than comparing them), selective (customers never take into account all the attributes of the channels) and subjective (the channel image attributes taken into account differ in number and quality from one type of customer to another).Originality/valueContrary to what the literature assumes, without ever demonstrating it, full integration does not imply that the retailer in question homogenizes or even matches up all the attributes of its channels. The retailer is thus able to act on attributes that promote this integration, while being relatively free to cultivate the incongruence of other attributes more likely to smoothly guide customers to a particular channel – in other words, a path midway between cross-channel and omnichannel.

Perbaikan Visibilitas pada Citra Berkabut Kawah Gunung Berapi Kelud Menggunakan Color Attenuation Prior

Mount Kelud is one of the volcanoes that erupted in 2014. To observe the activity, CCTV has been installed in the crater peak of Mount Kelud. The crater of Mount Kelud emits gases coming from the bottom of the crater. The gas makes CCTV surveillance undisturbed so that the resulting image will have noise. By using dehazing, visibility can be improved so that the resulting image can be seen clearly. The method used for this operation is Color Attenuation Prior. In the early stages, there is a dark channel process that works to turn low-intensity pixels dark. The second step is to estimate the atmospheric light from the dark channel image. This process is almost in parallel with the estimation of the depth map. The fourth step is estimating the transmission map, which functions to transmit low-intensity pixels to high-intensity pixels. The last one is the radiance recovery scene. The results show that the foggy image is successful, and it eliminates the fog effect, thus enhancing the visibility of the image. And from questionnaire results, we got 80 % positive results from all respondents. Further research so that it can be applied directly or in real-time.

Bi-channel image registration and deep-learning segmentation (BIRDS) for efficient, versatile 3D mapping of mouse brain

We have developed an open-source software called bi-channel image registration and deep-learning segmentation (BIRDS) for the mapping and analysis of 3D microscopy data and applied this to the mouse brain. The BIRDS pipeline includes image preprocessing, bi-channel registration, automatic annotation, creation of a 3D digital frame, high-resolution visualization, and expandable quantitative analysis. This new bi-channel registration algorithm is adaptive to various types of whole-brain data from different microscopy platforms and shows dramatically improved registration accuracy. Additionally, as this platform combines registration with neural networks, its improved function relative to the other platforms lies in the fact that the registration procedure can readily provide training data for network construction, while the trained neural network can efficiently segment-incomplete/defective brain data that is otherwise difficult to register. Our software is thus optimized to enable either minute-timescale registration-based segmentation of cross-modality, whole-brain datasets or real-time inference-based image segmentation of various brain regions of interest. Jobs can be easily submitted and implemented via a Fiji plugin that can be adapted to most computing environments.