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摘 要 随着科学技术的不断发展与现代战争的需要，以及红外搜索与跟踪系统(IRST)具有的诸多优点，使得红外搜索与跟踪系统已经成为当今世界精确制导技术发展和研究的主流方向。 当前的红外搜索与跟踪系统中存在的主要问题包括：大规模数据处理量与系统要求实时处理的矛盾；虚警率上升时系统处理时间成指数趋势上升，容易引起系统拥塞的问题；低信噪比下如何有效地检测到目标的问题。本文根据红外图像的基本特征、信息处理方法研究发展的现状，针对以上这些主要问题以及工程实际应用的基本要求，在红外图像预处理、点目标检测与跟踪信息处理系统设计等方面，进行了系统的深入的理论研究及计算机模拟，提出了一些快速而实用的算法，解决了系统大规模处理数据量与实时处理的矛盾；当虚警率上升时系统处理时间也不会急剧增加，使得系统在高虚警率下也可以实时应用，从而为解决工程实际问题提供了一些新的有效方法。 本文的主要的任务是对近距离运动目标进行方位探测,主要研究内容有:首先，图像预处理。对采集到的红外图像进行图像滤波、灰度变换、图像增强等算法，减少图像中的噪声和杂波，来提高图像信噪比，突出目标，抑制背景等，为后续工作做准备。其次，本毕业论文通过对常用图像预处理方法包括空间域滤波方法及频率域滤波方法的分析比较，针对实际情况进行算法的改进，选择了基于数学形态学滤波的背景抑制的方法对图像进行预处理。接着，对预处理图像进行阈值分割,得到目标图像的具体坐标。最后算出方位角。8204
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关键字：红外图像，形态学滤波，阈值分割，方位探测 Abstract
With the continuous development of science and technology and the
needs of modern warfare, as well as infrared search and track system (IRST)
has many advantages, infrared search and track system has become
mainstream in today's world of precision-guided technology development
and research directions.
The main problems in the infrared search and tracking system include:
the massive amount of data processing and system requirements for
real-time processing of contradictions; system false alarm rate
processing time of an exponential trend rise, likely to cause system
congestion problems; low signal to noise how to effectively detected the
target. Based on the basic characteristics of the infrared images,
information processing method of the status of research and development
for these major issues and the practical application of engineering the
basic requirements in the infrared image pre-processing, point target
detection and tracking information processing system design, the system's
in-depth theoretical studies and computer simulation, presented a fast
and practical algorithm to solve the contradiction between the
large-scale deal with the amount of data and real-time processing; system
processing time when false alarm rate will not dramatically increase,
making in high false alarm rate in real-time applications, and offers some
new and effective methods to solve practical engineering problems.
The main task is to close moving target orientation detection, the
main contents are: First, the image pre-processing. Infrared image
acquisition to image filtering, gray transform, image enhancement
algorithms to reduce image noise and clutter, to improve the image SNR,
highlight the target, and suppress the background, follow-up preparation.
Second, through analysis of commonly used image pre-processing methods
include spatial filtering and frequency domain filtering method compared
with the actual situation Algorithm selected based on morphological