Research on spatial-variant property of bistatic ISAR imaging plane of space target

The imaging plane of inverse synthetic aperture radar （ISAR） is the projection plane of the target. When taking an image using the range-Doppler theory, the imaging plane may have a spatial-variant property, which causes the change of scatter＇s projection position and results in migration through resolution cells, In this study, we focus on the spatial-variant property of the imaging plane of a three-axis-stabilized space target. The innovative contributions are as follows. 1） The target motion model in orbit is provided based on a two-body model. 2） The instantaneous imaging plane is determined by the method of vector analysis. 3） Three Euler angles are introduced to describe the spatial-variant property of the imaging plane, and the image quality is analyzed. The simulation results confirm the analysis of the spatial-variant property. The research in this study is significant for the selection of the imaging segment, and provides the evidence for the following data processing and compensation algorithm.

Marine target detection based on Marine-Faster R-CNN for navigation radar plane position indicator images

As a classic deep learning target detection algorithm,Faster R-CNN(region convolutional neural network)has been widely used in high-resolution synthetic aperture radar(SAR)and inverse SAR(ISAR)image detection.However,for most common low-resolution radar plane position indicator(PPI)images,it is difficult to achieve good performance.In this paper,taking navigation radar PPI images as an example,a marine target detection method based on the Marine-Faster R-CNN algorithm is proposed in the case of complex background(e.g.,sea clutter)and target characteristics.The method performs feature extraction and target recognition on PPI images generated by radar echoes with the convolutional neural network(CNN).First,to improve the accuracy of detecting marine targets and reduce the false alarm rate,Faster R-CNN was optimized as the Marine-Faster R-CNN in five respects:new backbone network,anchor size,dense target detection,data sample balance,and scale normalization.Then,JRC(Japan Radio Co.,Ltd.)navigation radar was used to collect echo data under different conditions to build a marine target dataset.Finally,comparisons with the classic Faster R-CNN method and the constant false alarm rate(CFAR)algorithm proved that the proposed method is more accurate and robust,has stronger generalization ability,and can be applied to the detection of marine targets for navigation radar.Its performance was tested with datasets from different observation conditions(sea states,radar parameters,and different targets).

Light Field Virtual View Rendering Based on EPI-Representations

Image-Based Rendering （IBR） is one powerful approach for generating virtual views. It can provide convincing animations without an explicit geometric representation. In this paper, several implementations of light field rendering are summa- rized from prior arts. Several characteristics, such as the regu- lar pattern in Epipolar Plane Images （EPIs）, of light field are explored with detail under 1D parallel camera arrangement. It is proved that it is quite efficient to synthesize virtual views for Super Multi-View （SMV） application, which is in the third phase of Free- Viewpoint Television （FTV）. In comparison with convolutional stereo matching method, in which the inter- mediate view is synthesized by the two adjacent views, light field rendering makes use of more views supplied to get the high-quality views.

Design and fabrication of silicon-tessellated structures for monocentric imagers

Compared with conventional planar optical image sensors,a curved focal plane array can simplify the lens design and improve the field of view.In this paper,we introduce the design and implementation of a segmented,hemispherical,CMOS-compatible silicon image plane for a 10-mm diameter spherical monocentric lens.To conform to the hemispherical focal plane of the lens,we use flexible gores that consist of arrays of spring-connected silicon hexagons.Mechanical functionality is demonstrated by assembling the 20-μm-thick silicon gores into a hemispherical test fixture.We have also fabricated and tested a photodiode array on a siliconon-insulator substrate for use with the curved imager.Optical testing shows that the fabricated photodiodes achieve good performance;the hemispherical imager enables a compact 160°field of view camera with >80% fill factor using a single spherical lens.

Sidelobe suppression in light-sheet fluorescence microscopy with Bessel beam plane illumination using subtractive imaging

The fluorescence from the out-of-focus region excited by the sidelobes of a Bessel beam is the major concern for light-sheet fluorescence microscopy （LSFM） with Bessel beam plane illumination. Here, we propose a method of applying the subtractive imaging to overcome the limitation of the conventional LSFM with Bessel beam plane illumination. In the proposed method, the sample is imaged twice by line scanning using the extended solid Bessel beam and the ring-like Bessel beam. By subtracting between the two images with similar out-of-focus blur, the improved image quality with the suppression of the Bessel beam sidelobes and enhanced sectioning ability with improved contrast are demonstrated.

Light field imaging for computer vision:a survey

Light field(LF)imaging has attracted attention because of its ability to solve computer vision problems.In this paper we briefly review the research progress in computer vision in recent years.For most factors that affect computer vision development,the richness and accuracy of visual information acquisition are decisive.LF imaging technology has made great contributions to computer vision because it uses cameras or microlens arrays to record the position and direction information of light rays,acquiring complete three-dimensional(3D)scene information.LF imaging technology improves the accuracy of depth estimation,image segmentation,blending,fusion,and 3D reconstruction.LF has also been innovatively applied to iris and face recognition,identification of materials and fake pedestrians,acquisition of epipolar plane images,shape recovery,and LF microscopy.Here,we further summarize the existing problems and the development trends of LF imaging in computer vision,including the establishment and evaluation of the LF dataset,applications under high dynamic range(HDR)conditions,LF image enhancement,virtual reality,3D display,and 3D movies,military optical camouflage technology,image recognition at micro-scale,image processing method based on HDR,and the optimal relationship between spatial resolution and four-dimensional(4D)LF information acquisition.LF imaging has achieved great success in various studies.Over the past 25 years,more than 180 publications have reported the capability of LF imaging in solving computer vision problems.We summarize these reports to make it easier for researchers to search the detailed methods for specific solutions.