While tracking dim and small moving targets in the electro-optical (EO) tracking system, the numerous false alarms resulted from the low signal-to-noise ratio would seriously debase the performance of target recognition and tracking. The probabilistic data association filter in conjunction with a maximum likelihood approach (PDAF-ML) has been applied effectively to low observable or dim target motion analysis. Whereas, the PDAF-ML supposes that the amplitude of target is not correlative among different sampling instants, and that the greater the amplitude value is, the greater the probability of being the target of interest would be. In the EO imaging tracking system, the amplitude information and the motion of target are consistent and highly correlative in a short period. To resolve the problem that the PDAF-ML is inconsistent with the EO imaging tracking system, the two features, namely, the amplitude information and the motion as well as their consistency, are modeled as Markov stationary random signals and are fused by means of PDAF. Experiments are carried out, and the results show that, with the proposed approach, the uncertainty of trajectory association would be largely decreased, and the performance of target recognition and tracking could be significantly improved.
Segmentation and restoration of highly noisy images is a very challenging problem. There are a number of methods reported in the literature, but more effort still need to be put on this problem.
In this paper we describe the development and implementation of a new effective approach to segmentation and restoration of imagery with pervasive, large amplitude noise. The new approach is based on the recently developed stabilized inverse diffusion equations (SIDE) and mathematical morphology. First, we find an optimized SIDE force function. Secondly, we segment the image to several regions accurately using the SIDE method. Finally a grayscale mathematical morphological filter combined with SIDE is assigned to the initial image data in each region to suppress the noise and to restore the total image. A test study based on available database is presented, and the results so far indicate that this approach to highly noisy imagery segmentation and restoration is highly effective.
This paper presents the numerical analysis about the thermal effects, produced by the high-energy laser in a beam control system, on the laser beam propagation. The propagation of laser is described by the paraxial wave equations, solved by the phase-screen technique and the FFT method. The thermal turbulence motion and the air density variation are governed by the complete Navier-Stokes equations, so that the variety factors could be in consideration. The Navier-Stokes equations are solved by using the LU-SGS factorization technique. The methods could be used for other kinds of aero-optical problems. The numerical results show that, with the additional initial thermal-phase, the energy concentration and the quality of the laser beam at far field would be prominently degraded for the typical situations.
Dim point targets detection in highly cluttered backgrounds is a challenging problem. In this paper we describe the development and the implementation of a new effective methodology to detect moving point targets in infrared or visual images. The new approach is based on mathematical morphology and motion analysis. First, the image is filtered by means of gray-scale morphology in order to reject background objects. Then, with the residual image a motion analysis based on trajectory conjunction is carried out to extract the potential point like moving targets. In the motion analysis stage we define a function to describe the characteristics of moving targets, and by this means a strategy is constructed to judge whether or not a given area contains the potential moving target. Through motion analysis, the non-target points are kicked out while the true target points are detected out after merely several frames of image. This approach doesn’t depend on threshold techniques and requires no assumptions about the behavior of the target motion. The only limitation is that the target’s speed doesn’t exceed several pixels per frame. A test study based on available database is presented and the results so far indicate that this approach to detect moving point target is highly effective.
It is to investigate molecule interactions between antigen and antibody with ellipsometric imaging technique and demonstrate some features and possibilities offered by applications of the technique. Molecule interaction is an important interest for molecule biologist and immunologist. They have used some established methods such as immunofluorescence, radioimmunoassay and surface plasma resonance, etc. to study the molecule interaction. At the same time, experimentalists hope to use some updated technique with more direct visual results. Ellipsometric imaging is non-destructive and exhibits a high sensitivity to phase transitions with thin layers. It is capable of imaging local variations in the optical properties such as thickness due to the presence of different surface concentration of molecule or different deposited molecules. If a molecular mono-layer (such as antigen) with bio-activity were deposited on a surface to form a sensing surface and then incubated in a solution with other molecules (such as antibody), a variation of the layer thickness when the molecules on the sensing surface reacted with the others in the solution could be observed with ellipsometric imaging. Every point on the surface was measured at the same time with a high sensitivity to distinguish the variation between mono- layer and molecular complexes. Ellipsometric imaging is based on conventional ellipsometry with charge coupled device (CCD) as detector and images are caught with computer with image processing technique. It has advantages of high sensitivity to thickness variation (resolution in the order of angstrom), big field of view (in square centimeter), high sampling speed (a picture taken within one second), and high lateral resolution (in the order of micrometer). Here it has just shown one application in study of antigen-antibody interaction, and it is possible to observe molecule interaction process with an in-situ technique.
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