新型低噪声CCD信号处理演示验证平台
发布时间：2018-12-26 09:38
【摘要】：CCD作为获取图像信号的主要器件,在可见光成像领域被看作是最有前途的探测器件,已经应用于日常生活、军事、航天等各个领域,尤其是在高分辨率可见光遥感卫星上得到了非常广泛的应用。为了获得高质量的遥感图像,对CCD成像电子学系统的信噪比提出了很高的要求。目前国内外的遥感卫星CCD成像电子学系统主要采用相关双采样(CDS)技术来降低CCD成像电路的噪声,但该方法对所能取得的效果已基本上达到了极限范围,提升空间极其有限。虽然可以采用电子信息系统通过各种算法对图像进行进一步的降噪处理,但该方法通常会滤除图像中的高频分量,影响图像的MTF。为此,本文提出了一种基于CCD像素信号处理的新型低噪声CCD成像电子学系统的实现方案。在本文中,首先运用MATLAB对该新型成像算法进行了仿真验证;其次,搭建了主要由FPGA和高速A/D实现的硬件平台;再次,通过对该算法进行研究分析,提出了实现该算法的电路结构,并最终在FPGA内部实现;最后,在搭建的硬件平台上,通过实验验证了该算法。实验证明该新型低噪声CCD成像方法是有效可行的,不仅可以有效地提高CCD成像的信噪比,而且不会影响图像的MTF。文中所做的工作可以为后续的研究及优化提供了基础。
[Abstract]:As the main device for obtaining image signal, CCD is regarded as the most promising detector in the field of visible light imaging, and has been applied in many fields such as daily life, military affairs, aerospace and so on. Especially in high resolution visible light remote sensing satellite has been widely used. In order to obtain high quality remote sensing images, the signal-to-noise ratio (SNR) of CCD imaging electronic system is very high. At present, CCD imaging electronic system of remote sensing satellite at home and abroad mainly uses correlated double sampling (CDS) technology to reduce the noise of CCD imaging circuit, but the effect of this method has basically reached the limit range, and the lifting space is extremely limited. Although the electronic information system can be used to further de-noising the image through various algorithms, this method usually filters the high-frequency components in the image and affects the MTF. of the image. A new low noise CCD imaging electronic system based on CCD pixel signal processing is proposed in this paper. In this paper, we first use MATLAB to simulate the new imaging algorithm. Secondly, we build a hardware platform which is mainly realized by FPGA and high speed A / D. Thirdly, through the research and analysis of the algorithm, the circuit structure of the algorithm is put forward, and finally implemented in FPGA. Finally, the algorithm is verified by experiment on the hardware platform. The experimental results show that the new low-noise CCD imaging method is effective and feasible. It can not only improve the signal-to-noise ratio of CCD imaging, but also not affect the MTF. of the image. The work done in this paper can provide a basis for further research and optimization.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP751
本文编号：2391900
[Abstract]:As the main device for obtaining image signal, CCD is regarded as the most promising detector in the field of visible light imaging, and has been applied in many fields such as daily life, military affairs, aerospace and so on. Especially in high resolution visible light remote sensing satellite has been widely used. In order to obtain high quality remote sensing images, the signal-to-noise ratio (SNR) of CCD imaging electronic system is very high. At present, CCD imaging electronic system of remote sensing satellite at home and abroad mainly uses correlated double sampling (CDS) technology to reduce the noise of CCD imaging circuit, but the effect of this method has basically reached the limit range, and the lifting space is extremely limited. Although the electronic information system can be used to further de-noising the image through various algorithms, this method usually filters the high-frequency components in the image and affects the MTF. of the image. A new low noise CCD imaging electronic system based on CCD pixel signal processing is proposed in this paper. In this paper, we first use MATLAB to simulate the new imaging algorithm. Secondly, we build a hardware platform which is mainly realized by FPGA and high speed A / D. Thirdly, through the research and analysis of the algorithm, the circuit structure of the algorithm is put forward, and finally implemented in FPGA. Finally, the algorithm is verified by experiment on the hardware platform. The experimental results show that the new low-noise CCD imaging method is effective and feasible. It can not only improve the signal-to-noise ratio of CCD imaging, but also not affect the MTF. of the image. The work done in this paper can provide a basis for further research and optimization.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP751
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