The multi-primary-color display faces the problem of color conversion between the device-dependent color space and the standard color space. A color conversion method based on BP-neural-network with luminance classification is proposed, and the conversion model from CIE standard (X,Y,Z) space to multi-primary-color (K1,K2,…,Kn) space is established. In this model, the (X,Y,Z) color space is decomposed into several two-dimensional subspaces according to the luminance factor Y of the training samples, and a series of BP-networks are established according to the luminance factors. Thus, this model overcomes the metamerism problem due to the color conversion from low dimensional space to high dimensional space. The validation experiment for this model is carried out using a five-primary-color LED display system. Firstly, on the bases of the actual chromaticity parameters of the five-primary-color LED display system, a linear conversion model for the color conversion between (K1,K2,K3,K4,K5) color space and (X,Y,Z) color space is established. Furthermore, the typical training set and testing set are generated according to the minimum color difference matching principle, and the BP neural networks are trained and tested. The results show that the average CIE1976L*a*b* color difference of the training set is below 6.37, and it needs further improvement. This study provides an effective approach for the color conversion of multi-primary-color display.

Revealing the motion of laser pulses between photoresists at ultrafast time scales with two-dimensional spatial resolution will help to understand the laser processing and optimize the process. However, most existing imaging technologies for recording the motion of laser pulses in photoresists suffer from the problems such as requiring multiple repeated shots or limited time resolution. To overcome these problems, compressed ultrafast photography (CUP) is proposed to capture the motion of laser pulses in photoresists. The experimental result shows that the motion process of non-repeatable events can be captured with single shot at the time-resolution about 1.54×1011fps, the depth of the imaging sequence reaches hundreds of frames.

A novel full-color transparent display screen based on the plasmon resonance and coupling effect of silver nanoparticles is proposed. Firstly, it shows that the optimized silver particles can support three scattering peaks respectively in the red, green and blue wavebands, which can be used to enhance the performance of full-color transparent display. Secondly, It experimentally demonstrates that, through a simple solution thermal method, the optimized silver nanoparticles can be embedded in the transparent matrix material to form a transparent display screen. The projector-to-screen projection test further proves that this screen indeed presents the full-color display with high transparency, high brightness and wide viewing angle. In addition, It also demonstrates that the silver nanoparticles have the dipole-type far-field scattering patterns at the three resonance wavelengths of red, green and blue due to the plasmon resonance and coupling effect, which well explains the reasons of the display screen with high brightness and wide viewing angle. The transparent display screen proposed r with the characteristics of high transparency and brightness, wide viewing angle, simple preparation process and low cost, will have potential applications in the field of transparent display.

As the number of initial structures is not enough for optical designers need, it is significant that methods of freeform surface are studied, because freeform surface is able to eliminate aberrations greatly. The design methods of initial structures are usually ray tracing or numerically solving of differential equations to construct point clouds, it is complex and costing largely of computing. A new method deriving the formulas of freeform surface in a view that optical system changes wave front was presented, and an infrared off-axis optical system with large relative aperture and wide working spectrum 3~12μm, focal length is 300mm, F/2.5, full field of view is 2.04°×2.56° was designed using this method. This system is with high quality of image (diffraction limit) and 100% cold stop efficiency, 0.059λ@3.67μm average RMS wavefront error.

The objective lens of the optical pickup is widely used in optical storage systems. Holographic optical storage uses holography to record and reconstruct information for storage purposes. The objective lens used in this process requires a high resolution and the commercially available objective lenses do not meet the requirements. Since both recording and reading are on the holographic recording material, the refractive index and thickness of the holographic material will impact the resolution and focusing efficiency of the objective lens. "Dual beam holographic optical storage" requires an objective lens of the optical pickup with high resolution and focusing efficiency in the dual working wavelengths mode of the beam. In order to fulfill such requirements, this study demonstrates the design of a dual-wavelength aspheric objective lens of optical pickup for holographic optical storage which is composed of an aspherical and spherical mirror by using the Zemax OpticStudio. The two working wavelengths are 532nm and 650nm and the focal length is greater than 4mm but less than 6.2mm. The numerical aperture is greater than 0.5, the MTF is greater than 0.4 within the spatial frequency of 900lp/mm, and the root means square of the wave surface difference obtained by focusing on the holographic material is less than 0.07λ. Regarding the above technical indicators, the designed objective lens has a high resolution and imaging quality. This design provides a new idea for the design of holographic optical storage lens.

An off axis reflective collimator is designed for multi-parameter detection of white light sights. In order to address the problem of large error of the primary mirror face form due to low frequency vibration of the collimator under operating condition, a flexible support scheme for the back of the primary mirror is proposed, and the important structural parameters of the flexible support for the primary mirror are optimized. At the same time, the properties of the RTV adhesive is analyzed and the effective property and equivalent module multiplier of the annular RTV adhesive are calculated. The simulation results show that the RMS and PV values of the surface error of the primary mirror assembly are 0.79nm and 3.66nm, respectively, under the action of 1-g gravity, which can meet the system requirements for wavefront aberration of the collimator. The first mode frequency of the whole collimator is 496.38Hz, which has a good ability to resist low frequency vibration. Under the action of thermal coupling, the face form errors of the primary mirror face form variations all meet the design requirements of RMS valueand ≤λ/30 PV value ≤λ/10.Under the harmonic response analysis, The maximum stress under 1000N force is less than the yield limit of the material. The dynamic performance and surface accuracy of the off-axis reflector collimator with flexible support can meet the design requirements.

In the process of three-dimensional scanning and imaging of objects on the conveyor belt, the convenience and accuracy of the displacement calibration method have a very important impact on the final imaging accuracy and efficiency, but the traditional displacement calibration method requires knowing the movement speed of the displacement platform and conveyor belt or strictly controlling the precise displacement between the calibration plates in the two calibration pictures, which makes the calibration process more complicated. A displacement calibration method of linear structured light 3D scanning and imaging system specially used for object measurement on conveyor belts is proposed. This calibration method only needs to collect a series of displacement calibration pictures of the calibration plate moving with the conveyor belt, extract two pictures with a frame interval greater than 1 and record the corresponding number of frames to calibrate the single frame displacement. The basic principle and implementation method of the calibration method are introduced, the line scan monocular imaging system is built, and the double-step precision block is reconstructed in three dimensions. The experimental results show that the method is simple in principle, convenient in operation, faster in measurement speed and simple in operation, and the reconstruction error is less than 0.3mm. It is suitable for real-time three-dimensional measurement in various fields where the conveyor belt is the main means of transportation.

Aiming at the problem that the phase target calibration camera needs to collect multiple patterns to obtain phase, a camera calibration method based on color cross fringe is proposed. This method only needs one fringe image to complete the extraction of feature identification points at each calibration position. A red and blue cross fringe image is display on a LCD (liquid crystal display) and captured by a camera. The Fourier transform and multi-frequency heterodyne method are used to obtain the absolute phase in the horizontal and vertical directions. The internal parameters of the camera are calibrated by using the exact correspondence between the spatial position of the phase target and the absolute phase in the image. The interior parameters of the camera are optimized by a nonlinear least square method. The experimental results based on the re-projection error show that this method can achieve camera calibration quickly and accurately.

A double Sangac interference ring optical fiber pressure sensor based on vernier effect is proposed. The sensor uses polarization maintaining photonic crystal fiber (PM-PCF) as a sensitive unit to realize Sagnac interference and vernier effect for pressure sensitivity through different PCF lengths. The sensor uses PM-PCF embedded in the single-mode optical fiber to form the reference unit and pressure sensitive unit of the sensor, and the pressure sensing part of the Sagnac ring is packaged. The pressure characteristics of the parallel Sagnac ring pressure sensor are studied through experiments. The experimental results show that the maximum sensitivity of the pressure sensor is -54.491nm/MPa and the resolution is 0.367kPa in the pressure range of 0~2.4MPa. Compared with the Sagnac ring pressure sensor without vernier effect, its pressure sensitivity is amplified by 16.7 times. In addition, the sensor has the advantages of simple manufacture, solid structure and stable operation, which provides an alternative design scheme for the high-sensitivity pressure sensor.

Heart rate is an important indicator of human health. Detecting heart rate from face videos is a rapidly developing non-contact detection method, but the accuracy of the results is susceptible to noise such as changes of illumination and head movements of the subject. In order to eliminate the influence of noise and improve the accuracy of heart rate detection, a new idea is innovatively proposed: Illumination changes and head motion noise are used as targets for trend fitting and eliminated from the camera raw signal to achieve human heart rate signal extraction with high signal-to-noise ratio. In order to verify the feasibility of the proposed method, the value of the medical finger-clip pulse oximeter is used as the reference heart rate. By comparing the average signal-to-noise ratio at the reference heart rate and heart rate detection accuracy, the proposed method has increased by 9.60% and 37.19% compared with the POS method. Compared with the ICA algorithm, it has increased by 48.48% and 51.75%. Experimental results show that the new proposed method has better denoising ability and higher accuracy.

To achieve efficient thread pitch measurement, an area-based method is proposed to solve thread pitch measurement and evaluation based on the analysis of existing methods to solve thread pitch measurement by machine vision. The process starts by rotationally correcting the thread image to obtain the mid-diameter point using geometric relationships such as the area of the trapezoidal site of the tooth profile on the thread axis cross-section, then fitting the mid-diameter line using the least squares method, and finally combining this with the principle of inclusion to obtain the measured thread pitch. The data show that the area method is comparable to the average pitch measured by the contact gauge and the tool microscope, with a standard deviation of 0.9μm slightly greater than the standard deviation of 0.6μm measured by the indicator and much smaller than the standard deviation of 9.6μm measured by the tool microscope; the measurement efficiency of the area method is 1.9 times that of the indicator and 2.5 times that of the tool microscope. The area method is 1.9 times more efficient than the integrated measuring instrument and 2.5 times more efficient than the tool microscope.

Steam pipeline in thermal power plant is long-distance and high-temperature, so it is difficult to find the leakage point. A distributed temperature sensor system is built to monitor the temperature field of steam pipeline. The system can demodulate the temperature from the reflected light affected by the pipeline temperature according to the Raman principle, and the position of measuring point is confirmed through optical time domain reflection technology. Finally, Kalman algorithm is used to de-noise the temperature signal, the result show that it can reduce the system signal fluctuation to 1℃

In optical wireless communication system, photoelectric conversion is realized by photodetector at the receiver, and the noise in the detector will directly affect the photoelectric conversion efficiency. Based on the background of optical wireless communication, according to the generation mechanism of photodetector noise, this paper describes the shot noise, multiple generation compound noise, 1/f noise and thermal noise of the detector respectively, and gives the corresponding mathematical models. The noise models of avalanche photodetector, original negative signature detector, photomultiplier tube, four quadrant detector, quantum dot infrared detector and balance detector are analyzed respectively. Finally, the direction of further research in this field is pointed out.

Multi-antenna interferometric array utilizes multiple remote antennas to receive signals simultaneously to improve detection sensitivity and angular resolution. The multi-channel signal combination requires high-precision time synchronization between different channels. A multiplexing multi-channel time synchronization method is proposed. A single digital delay pulse generator is used to regenerate and distribute time signals, and the corresponding measurement and control algorithm is designed. While accurately measuring the transmission delay of multiple fiber optic links, stable time signals are distributed to multiple remote antennas. The experimental results show that the system has a ps level transmission delay measurement accuracy and a 20ps-level time signal distribution accuracy with 25km transmission. This solution can simultaneously support distributed systems with either local or remote digitization, effectively reducing the cost of the distributed synchronization system while ensuring time synchronization precision.

To address the problem that a single polarization image cannot provide sufficient information in a certain scene, a polarization image fusion algorithm based on dense gradient generative adversarial networks are proposed by combining the advantageous features of intensity image and line polarization degree image. A dense gradient convolution module is constructed using a densely connected convolution network and gradient operator, and the module is applied to the generator to enhance the texture details of the fused images; a loss function combining multi-scale structural similarity and L1 parametrization are used to improve the overall performance of the network. Qualitative comparison and quantitative analysis were performed on the ZJU-RGB-P dataset, and the experimental results showed that the proposed algorithm has better subjective visual perception, while all evaluation indexes were significantly improved.

Aiming at the problem that the existing single-image super-resolution methods tend to ignore the differences and relations between different structures and textures in the original image during the reconstruction process, resulting in the lack of texture details and artifacts in the generated high-resolution image, an Image Super-resolution Reconstruction Algorithm for Texture Details Recovery (TDRSR) is proposed.The method consists of gradient branch, texture branch and image super-resolution branch. Among them, the class attention module is used between the gradient branch and the texture branch to deal with the feature confusion problem of the two, and the mutual promotion of structural features and texture features is realized through the bidirectional feature fusion module, which is used as prior information to achieve texture details. purpose of information enhancement. In addition, the image super-resolution branch also helps the network to retain richer contextual information and texture details in the image by building a feature recovery module that utilizes both shallow and deep information. The method trains the network on the DIV2K dataset, and conducts test experiments on 5 benchmark test sets Set5, Set14, B100, Urban100 and MANGA109, the peak signal-to-noise ratio (PSNR): 37.88dB, 33.28dB, 32.0781dB, 31.89dB and 38.39dB, which are significantly improved compared to the results of other methods. The experimental results show that the method obtains effective reconstructed images and preserves more image details, generating super-resolution images with sharp edges and realistic details.

A generative adversarial network combining color prediction and semantic perception is proposed to address the problem of color haloing and region mis-coloring in texture details after colorization due to large modal differences between NIR and visible images in the colorization process. A dual branch generator is designed for color prediction and semantic perception, where the color prediction branch uses a residual network with jump connections and the semantic perception branch uses a dilated convolutional pyramid structure with semantic fusion. Different expansion rates can obtain multiple perceptual fields to extract multi-scale semantic features, and embed the perceived semantics into the color prediction branch to improve the semantic understanding of the model and improve the color haloing and region mis-coloring problems. A cyclic consistent semantic loss function is designed to constrain the consistency of semantic information in the generator. The algorithm performs performance experimental comparison as well as ablation experiments on an RGB-NIR scene dataset. Experiments show that this algorithm outperforms existing colorization algorithms in terms of PSNR, SSIM, and LPIPS evaluation metrics, and the coloring effect is more consistent with visual perception.