Blue phase liquid crystal elastomer (BPE) is a functional material integrating three-dimensional photonic crystal structure and rubber soft elasticity and has a wide application prospect in the field of liquid crystal photonics. However, the novel preparation method and elastic properties of BPEs need to be further investigated. On the basis of in-situ photopolymerization, BPE films with different mercaptan (EDDET) contents were prepared by introducing the click chemical reaction between EDDET and acrylate. The influence of EDDET content and UV curing on the lattice structure, thermal stability and optical properties of BP were systematically studied, in ddiion, the elastic properties and stress color change properties of BPE prepared with different EDDET concent were measured. The experimental results show that EDDET could effectively fill the disclination network of BP. With the increase of EDDET content, the thermal stability of BP was increased by 5 times. The UV light curing process would induce BP lattice deformation. As the EDDET content increased, the fracture length of BPE film was increased by 7 times, and the stress decreases by about 52 times with the same change of the Bragg reflection peak of BP. We believe that the BPE films prepared by this method has a wide application in the fields of intelligent bionics, sensing, anti-counterfeiting, lasing and so on.

Micropolarizer array (MPA) is the core component of division of focal plane polarimeter (DoFP). Compared with nano-wire-grid polarizer array, liquid crystal micropolarizer (LCMP) array has some unique advantages such as flexible design, simple process, good stability and show great potential to achieve not only cost-effective but also high precision polarization measurement and imaging. In this paper, we summarize the researches on LCMP array domestic and oversea in recent years. Here, three working principle of LCMP arrays: guest-host effect, polarization rotation and phase retardation as well as their structure are systematically elaborated. Different alignment structures of LCMP can achieve not only linear but full Stokes polarimetry. Finally, future development trends and key challenges of liquid crystal micropolarizer arrays and DoFP imaging technology are discussed.

Electronically controlled gradient refractive index liquid crystal lens (EC-GRIN-LCL)is an optical lens that can change the distribution of its spatial refractive index to zoom in out by controlling the electric field. Due to the properties of variable focal length, compact structure and excellent stability, it has been attracting intensive attention in the field of optical lenses. This review introduces the basic working principle of EC-GRIN-LCL and describes four types of liquid crystal lenses driving strategies: (1) by edge electric field, (2) by discrete multi-electrode, (3) by electrode with high resistance layer, and (4) by complete electrode layer or no electrode layer. By introducing, concluding and commenting on the representative instances of the four types of EC-GRIN-LCL, this review aims to provide the readers with a clear basic knowledge, a comprehensive development history and tendency, and a reference for further research of EC-GRIN-LCL.

If TFT array substrate has large via hole resistance and poor current withstanding properties, via hole is easy to burn up which will cause abnormal display. At present, the influencing factors and mechanism of the via hole resistance and current withstanding properties are not clear, which restricts the preparation and application of the via hole with good current withstanding properties. In this paper, the experimental results show that reducing block resistance of indium tin oxide film (ITO), reducing the slope angle of via hole and increasing contact area between ITO film and metal can reduce via hole resistance and improve current withstanding properties of the via hole. Combined with the analysis of via hole structure and mechanism, it is pointed out that the via hole resistance is mainly composed of ITO film resistance (RITO) and the via hole contact resistance (Rcontact). Either reducing block resistance of ITO film or the slope angle of via hole will reduce ITO film resistance (RITO), while increasing contact area between ITO film and metal will reduce the via hole contact resistance (Rcontact). The via hole current withstanding properties is worse in middle of the substrate because the ITO film block resistance and via hole slope angle are larger. Thicken ITO film, regulating insulating layer film quality and dry etching parameters to reduce slope angle and increase via hole contact area are effective ways the via hole resistance and improve the via hole current withstanding properties under the premise of meeting product optical quality standard.

In order to analyze the line image sticking of TFT-LCD, the influence of pattern’s data driving voltage on common voltage through capacitance (CDC) is studied. Firstly, according to the actual film distribution of array, the specific composition of capacitance in the film is described, and the equivalent circuit model of CDC is established. The CDC in actual working state is measured, and analyzed by the model effectively. Then, the method is established to measure the distortion of common voltage generated by checkerboard driving voltage and analyze the mechanism of line image sticking. Finally, the “black-gray-bar” pattern is set to maximize distortion, so as to analyze the formation process and influencing factors of distortion. The experimental results show that when TFT is turned off, TFT presents a high resistance state, CDC is the same as C0 (corresponding to overlapping metal line of data voltage and common voltage), which is 55 fF. When the TFT is turned on, it presents a low resistance state, CDC is connected in parallel by a storage capacitance and C0, which is 530 fF. When the TFT is in the intermediate state, the capacitance is the intermediate value obtained from the measure. The larger the capacitance of CDC is, the faster the conversion speed of data voltage is, and the larger the distortion is. It is found that reducing the conversion speed from 48 ns to 53 ns can reduce the distortion value from 2.67 V to 2.61 V.

The key factors affecting threshold voltage variation compensation are identified through analyzing the operation processes of a relevant voltage program LTPS AMOLED pixel circuit. The factors include charging time restriction on threshold voltage detecting process due to data voltage signal refreshing period, and accuracy loss of threshold voltage in voltage program caused by capacity increment of related TFTs. Circuit countermeasure to these adverse factors are put forward to extend the charging time through separating the threshold voltage detection from data voltage signal refreshing process, and to compensate the error due to capacity increment through a TFT with reversed capacity increment. In pixel circuit state simulation under a low grey level display state, the variation of OLED driving current of pixel circuit of separated threshold voltage detection and data voltage signal refreshing is less than a seventh current variation of the reference circuit, and the variation of OLED driving current with capacity increment compensation is about half the current variation of the pixel circuit without capacity increment compensation. The improving effects in samples demonstration are consistent with the trend of simulation results.

Aiming at the problem that the solution space of mapping function from low resolution image to high resolution image is extremely large, which makes it difficult for super-resolution reconstruction models to generate detailed textures, this paper proposes a image super resolution that combines dual attention and structural similarity measure. With the improved U-Net network model as the basic structure, the data augmentation methods for low-level vision tasks are introduced to increase sample diversity. The encoder is composed of a convolution layer and an adaptive parameter linear rectifier function (Dynamic ReLU). At the same time, a residual dual attention module(RDAM) is introduced, which forms a decoder together with the PixelShuffle module. The image is enlarged gradually through the up-sampling operation. In order to make the generated image more in line with the human visual characteristics, a loss function combined with structural similarity measurement criteria is proposed to enhance the network constraints. The experimental results show that the average PSNR of the quality of the reconstructed image on the Set5, Set14, BSD100 and Urban100 standard test sets is improved by about 1.64 dB, and the SSIM is improved by about 0.047 compared with SRCNN.The proposed method can make the reconstructed image texture more detailed and reduce the possible solution space of the mapping function effectively.

Dual-image reversible data hiding (RDH) has become an important research direction in the field of information security due to its better security, embedding rate and image visual quality. Bhardwaj et al. proposed a dual-image RDH algorithm on encrypted domain to further improve the security, but the embedding capacity of this algorithm is limited. In this paper, we propose a new embedding strategy by decomposing each pixel of an image into three units and encrypting them using the Paillier algorithm. According to the improved maximum distortion control coding table, the secret messages are embedded dynamically using the averaging method, i.e., the number of bits of secret information is varied for each embedding. The experimental results show that the embedding rate of our method is improved by 0.72 bpp compared with the method of Bhardwaj et al. and 0.25 bpp compared with the original maximum distortion control method. At the same time, the original image can be recovered losslessly, so the reversibility is guaranteed. It can meet the dual requirements of privacy protection and secret communication in high-capacity scenarios.

Micro-expression refers to the expression that people spontaneously generate when they want to hide their true emotions. The duration is within 1/5 s. Their facial muscles are short and small in amplitude. The limited data set makes feature extraction difficult. These factors bring huge challenges to its recognition. In response to these problems, this paper proposes a recognition method based on image preprocessing technology and dual-branch network. Firstly, an advanced face alignment network is used to obtain effective facial regions, and then Euler video magnification technology is used to capture the subtle changes in facial movements. Optical flow information is used as the feature of the video sequence, and the feature maps of different combinations of optical flow information are input into the two-branch classification network to obtain the expression label output. Experiments aere performed on the two public data sets of SMIC and CASME Ⅱ, and the leave-one-subject-out(LOSO) is employed for cross-validation. The accuracy can reach 0.545 and 0.584, respectively. The quantitative and qualitative analysis of the experimental results verify the effectiveness of the proposed method.

A low light level image enhancement algorithm based on double branch pyramid model is proposed. It is used to solve the problems of low brightness, serious loss of detail, over exposure and color distortion of the low light level image enhanced by existing algorithms. Firstly, the low-light level image is converted from RGB color space to HSV color space. Secondly, the low-light level image enhancement network of double branching pyramid network is constructed for the V component, and the image features are obtained adaptively. The network structure is composed of two parallel branches. The branch with hierarchical residual module can effectively enhance the brightness of V component, and the branch with feature pyramid attention module can obtain deep feature information. Finally, the information extracted from the dual-branch structure is fused, and the enhanced image is converted from HSV color space to RGB color space. The peak signal-to-noise ratio and the average structure similarity of the proposed algorithm on real images are 29.451 dB and 0.930 1 respectively, which are higher than other comparison algorithms. Experimental results show that the enhancement of the V component can effectively improve the image brightness and restore the image details.

The optical remote sensing image sea surface ship target detection is susceptible to cloud, island, sea clutter, shadow and other complex factors interference. At the same time, due to the large width of satellite remote sensing images, if the real-time detection and hardware transplantation needs to be met, the amount of computation and portability of the algorithm should be considered. In order to meet the needs of practical engineering, this paper proposes an adaptive fast ship target location and detection method based on visual saliency under complex background. Firstly, the algorithm adaptively obtains the global optimal scale based on image gradient, and obtains the global significance region through the spectral residual significance model. For the regions with poor segmentation effect due to global threshold in significant regions (Complex regions), the local complex regions are screened out by designing contour and other shape features, and the saliency map is further calculated. Then, the processing results are fused with the original significance map to obtain the final extraction results of suspected regions. Finally, the candidate regions are further distinguished using support vector machine. The results show that the proposed algorithm can effectively detect ship target areas with different sizes and directions under complex background, and the detection accuracy of the algorithm is 91.4% and the recall rate is 91.2%, which is better than most of the similar algorithms and close to the accuracy of the deep learning algorithm. At the same time, in terms of algorithm volume, the calculation amount and the number of parameters of the algorithm in this paper are far lower than those of most deep learning frameworks, which is more suitable for hardware transplantation. Meanwhile, the algorithm has stronger mobility and is easy to modify and maintain.

Aiming at the problem that the cooperative target is difficult to be clearly recognized by the camera in the large visual range rendezvous and docking of small satellites based on vision sensors, this paper designs a new integrated cooperative target, which can achieve high precision to resolve the relative poses of the binary stars from far to near in the measurement range of 100 m to 100 mm. Firstly, a cooperative target model is established to determine the type of cooperative target. Secondly, the PnP (Perspective-n-Point) algorithm is used to design the number and size of the cooperative target's feature points. Then, according to the constraint relationship between the camera's field of view, focal length and the cooperative target, the size of the cooperative target model is determined. Finally, it is verified by a combination of theory and experiment. The simulation experiment results show that the attitude error is less than 4.01°, and the position error is less than 7.57 mm when the object distance is 100 m. When the object distance is 100 mm, the attitude error is less than 0.06°, and the position error is less than 0.02 mm.