Three-dimensional （3D） imaging and display technology can obtain and save the three-dimensional information of objects and present stereoscopic realistic pictures. It has broad application prospects in consumer electronics， autono

Multifunctional and highly integrated all-fiber devices has promoted the development of lab-on-fiber technology. The rapid progress in the manufacturing technology has opened up a new avenue for the multifunctional plug-and-play f

The key fabrication technology for diffractive optical elements （DOE） was systematically investigated from the following four aspects： graphic data processing， advanced lithography， pattern transfer， and large-area integration wit

The metalens constructed by the micro-nano structure array is not only small and lightweight， but also has a multi-functional design that can be realized through a composite structure. The existing metalens diameters are generally

The modulation of the phase wavefront of geometric phase metasurface lenses does not depend on the cumulative phase of the propagation process. However， it affects the local polarization state through the space-variant unit struct

In the processing of infrared optical microstructured surfaces， the hard， brittle， and difficult-to-machine properties of infrared optical materials and the complex geometric properties of microstructured surfaces lead to uneven a

To achieve high-efficiency and low-defect machining of fused silica optics， the material removal characteristics and surface quality formation mechanism based on magnetically assisted polishing technology were studied. Magnetic po

It is difficult to suppress the noise in static state of the existing filtering algorithm. Moreover， motion compensated filtering algorithm fails to effectively suppress noise. To solve these problems， a video denoising algorithm

To remove the mixed noise from remote sensing images， a wavelet multifractal denoising algorithm was developed. The algorithm mainly uses wavelet analysis for signal decomposition and multifractal to extract image features. First，

To extract the deep discrimination features from hyperspectral images， many labeled samples are often required； however， it is difficult to label samples in hyperspectral image. By using the characteristic of combining image with