We present a dynamic DNA coding multi-image encryption algorithm based on integer lifting wavelet transform and compound chaos. In the encryption process, the low-frequency sub-bands of four plaintexts are extracted to get a combined image containing the multiple plaintext image information. With the help of a chaotic system, the pixel positions and pixel values of the combined image are modified by the permutation and the diffusion operations. Then we divide the image into equal-sized blocks, and the dynamic DNA coding method is used to complete the final encryption. To enhance security, we employ the RSA algorithm to protect the keys used in our encryption algorithm. Simulation results and security analysis demonstrate the robustness and the security.
A diffractive waveguide based on surface relief grating is one of the most significant components for near-eye displays (NEDs). Here, we propose a colorful NED system using meta-grating as the coupler to achieve high exit-pupil brightness uniformity and color uniformity. The whole system has a lightweight and compact configuration and allows for flexible integration with ordinary smart glass. Our work provides a feasible way to design a colorful and miniaturized NED.
We employ a Bayesian optimization (BO) approach coupled with electromagnetic solver to optimize the photonic nanojets (PNJs) respectively generated by a 2D cuboid and a 3D concentric cylinder. The operating wavelength is selected atλ = 632.8 nm. By optimizing a five-layer cuboid, we achieved a narrow PNJ with waist at the full width at half-maximum (FWHM) about w ~ 0.2λ and an ultra-long PNJ with a beam length 123λ , respectively. Whereas by optimizing 3D concentric cylinder, we achieved a narrow PNJ with waist at FWHM about w ~ 0.22λand ultra-long PNJ with a beam length 78λ , respectively. Furthermore, we explore the physics behind the PNJ phenomenon, such as the fundamentals of extreme PNJ generation and the relation between the objective intensity profile and the refractive index gradients across the structure. The proposed approach presents an alternative approach to the design of various photonic nanostructures and may provide conventionally-inaccessible physical insight to their functionalities.
Aiming at the problem of mutual restriction between the quality of image and the equipment size in the current near-eye display (NED) system, we propose a NED system based on metasurface. We design a colorful NED system for MR/AR applications using all-dielectric metasurface and retina display technology. Based on the principle that metasurface can accurately control the wavefront, the system presents high-quality images while achieving lightweight and compact configuration like an ordinary pair of glasses. The semi-transparent metasurface with a size of 10mm×10mm is placed 15mm away from the eyes. Results show that the system could effectively enable monochromic and colorful object display onto the retina, and therefore allow clear images to be seen. With further optimization design, such system could provide a feasible solution for colorful NED system with miniaturization.
KEYWORDS: Video, Video compression, Spatial resolution, Reconstruction algorithms, Image restoration, Data acquisition, Imaging systems, Digital micromirror devices, Data compression
Single-pixel camera,taking advantage of the technique of compressive sensing, is a new imaging scheme proposed in recent years. It essentially uses a single-point detector to replace the traditional array detector of the camera and a few measurements to complete the image reconstruction. In this paper, we propose a dual-channel acquisition system based on the bidirectional reflection characteristics of spatial light modulator and build such a compressive imaging configuration with substantial noise suppression. In addition, we conducted a video reconstruction study based on this system and compared two reconstruction strategies. One is based on video frame decomposition, which decomposes the video sequence into individual video frames and converts the video reconstruction into a sequence of static image reconstructions. The other is to design a fusion matrix, using its low-dimensional matrix for video preview to obtain motion estimation, and then obtaining the reconstructed video through its high-dimensional matrix. We compared the performance of the two approaches by analyzing the data from the actual experimental platform, and realized real-time video capturing and recovery at 40 fps at resolution 128*128.
In this work, based on the principle of blind deconvolution, and considering the inherent structure of the blur kernel, an automatic relevance determination (ARD) model is used to determine the prior model based on the gradient, instead of intensities of the blur kernel. The results show that the proposed ARD model on gradient can improve the kernel quality and thus produce better de-blurred image. Compared with the case of using the intensity for ARD, the proposed algorithm gives better blur kernel estimation and show robustness against non-Gaussian noise. As concrete examples, we demonstrate that the proposed method is applicable to image restoration on the scenario of camera shake, object motion and defocused blurring.
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