IOE OpenIR  > 光电技术研究所博硕士论文
Thesis Advisor张启衡
Degree Grantor中国科学院光电技术研究所
Place of Conferral光电技术研究所
Degree Discipline物理电子学
Keyword目标检测 低对比度图像增强 杂波抑制 等效椭圆 Fpga
Abstract小目标检测与识别技术一直是光电探测跟踪系统的关键技术之一。本论文围绕强杂波背景条件下的小目标检测技术,展开深入而细致的研究,旨在提出一些有针对性的技术路线和方法,以解决应用领域中的一些难点。 根据小目标的成像模型,首次提出了基于点扩散函数噪声抑制技术。通过分析图像的高斯偏移模型,有效提取出图像中与目标高斯模型最相似的候选目标点,抑制背景和杂波。 利用图像等效椭圆的差别,本文从模式识别的形状匹配角度提出了一种新的目标识别算法。该算法利用图像中目标和伪目标点在等效椭圆性质上的不同,去除与目标匹配较差的噪声点,从而识别出匹配度较高的目标点。 本文在小目标图像的图像增强、噪声抑制和目标分割等方面,提出了一些新的技术和方法。仿真实验表明,相比较其他的图像处理算法,能取得更好的效果。 根据工程应用的实时性要求,论文细致的分析了实时跟踪平台(DSP+FPGA)的结构,结合小目标检测方法应用的特点,解决了在FPGA中实现指数求解的难题,进而在FPGA中实现了低对比度小目标图像的增强算法,实现了检测算法的实时应用;通过DSP的EMIF口的异步方式传递数据到FPGA,实现参数的实时改变,从而可以改变图像的增强效果;试验取得了满意的效果。
Other AbstractThe technique of small dim target detection and recognition has been the key technique of the electro-optical detecting system. Aiming at the detection and recognition of small target in heavily clutter and background light imagery, this dissertation developed some effective methods and algorithms to solve some difficulties in the application area. The clutter suppression method based on the point spread function (PSF)was firstly proposed, which can obtain the targets of candidacy that has the same Gauss model furthest as the real target and suppress the background light and clutter by analyzing the Gauss excursion of the image. A new method to detect small target was put forward by utilizing the difference of the equivalent ellipse according to the shape match algorithms of pattern recognition theory, which can detect the target and eliminate the noise based on the characteristics of it. Some new technologies and methods were presented aiming at the steps of the image processing of the small target image, including image enhancement, clutter suppression and target segment. Experiments proved the preferable performance compared to the traditional algorithms. Finally, the small target detection platform based on DSP+FPGA is introduced in order to satisfy the real-time performance in practice. The key problem of exponential function implement on the FPGA was worked out and the image enhancement algorithm was fulfilled on the platform successfully combined with the characteristics of small dim target detection, so the engineering-oriented application of the algorithm was obtained; The parameters could be transferred to the FPGA across the EMIF of DSPs so as to alter the enhancement performance.
Document Type学位论文
Recommended Citation
GB/T 7714
陈中坤. 强杂波背景条件下小目标检测技术研究[D]. 光电技术研究所. 中国科学院光电技术研究所,2007.
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