探讨了红外图像中的弱小目标检测问题。
Detection of dim small targets in infrared images was addressed.
弱小目标检测是当今研究的热点问题之一。
提出了一种红外图像序列中运动弱小目标检测的新方法。
A new detection method for moving dim small targets in infrared image sequences is presented.
当目标处于复杂背景中时，红外弱小目标检测将变得更加困难。
Detection of infrared dim small target becomes rather difficult if the target lies in a complicated background.
提出了一种新的基于模糊分类的红外云层背景弱小目标检测方法。
A new method is proposed to detect infrared small and dim targets in cloud cluster image based on fuzzy classification.
对红外弱小目标检测方法的研究依然是一个很具有挑战性的课题。
The research of infrared weak small target detection is still a issue with great challenge.
通过与传统弱小目标检测方法的对比实验，验证了方法的有效性。
Compared with traditional test methods, the method can effectively suppress the background, while enhancing the target.
提出了一种利用局部灰度特征分析进行红外弱小目标检测的新方法。
A new method of infrared small and dim target detection is proposed.
根据序列图像中运动弱小目标的相关性，提出一种弱小目标检测的方法。
A detection method for small target is proposed according to the correlation of the small moving target in sequential images.
针对红外运动弱小目标，本文提出了基于邻域判决的红外运动弱小目标检测方法。
The detection of moving weak and small targets in IR sequences is discussed and studied finally, based on a neighborhood judging method.
但当背景起伏较大时，基于背景预测的弱小目标检测方法的检测性能会受到影响。
Since background in the IR images changes quite slowly, it is meaningful to detect targets by background prediction.
本文着重对天空背景和复杂海天、海面背景下的弱小目标检测算法进行了深入研究。
This thesis researches the detection algorithm of small target under sky background and sea-sky background.
首先，综述了红外弱小目标检测技术的国内外研究状况，分析了红外成像机理及特点。
Firstly, the state of arts of infrared weak and small targets detection is reviewed in domestic and abroad, and the mechanism of infrared imaging is analyzed.
针对红外图像的特点及分形分维的特性，提出了基于分维像的红外弱小目标检测方法。
Based on the features of infrared image and the speciality of fractal dimension, a method of detection infrared dim small target based on fractal dimension was presented.
为解决复杂背景下的红外弱小目标检测问题，提出了一种基于分维和三阶特征量的改进方法。
We propose an improved algorithm based on fractal dimension and third-order characterization to detect dim target with cluttered background in an infrared (IR) image.
红外弱小目标检测技术是红外搜索与跟踪、红外预警、红外制导等防御和武器系统中的核心技术之一。
Dim and small moving targets detection of IR sequence images is a key technique for the IR detection and tracking, alarming, guiding system.
大量的实验结果证明，这几种方法对复杂背景下的红外弱小目标检测很有效，并且准确性高、实时性强。
A lot of experimental results demonstrate that several methods presented infrared dim and small targets detection in the complex background are very effective, exact.
本论文课题来源于国家自然科学基金项目“基于背景预测的红外弱小目标检测技术”(60007007)。
The project of this thesis is supported by the National Science Foundation of China, named "Detection of small and dim target in infrared based on background prediction" (60007007).
文章总结了自适应背景预测技术在红外弱小目标检测领域的典型应用，分析了线性和非线性自适应算法的优缺点。
The typical applications of adaptive background prediction technology in weak and small infrared target detection are summarized in this paper.
其次，利用小波多分辨分析特性，提出了基于小波分析的自适应门限检测方法，有效地提高了红外弱小目标检测性能。
Secondly, a new method of infrared weak and small targets detection based on wavelet and adaptive threshold is proposed with an effective improvement detection of performance.
针对红外搜索跟踪系统对复杂云层背景条件下红外弱小目标检测问题，提出了一种低虚警率的弱小目标稳健检测算法。
For the infrared dim small target detection in complex cloud background of IRST, a robust algorithm of low false alarm is proposed.
该方法通过判断图像局部灰度包络曲面是否具备二维高斯函数曲面特征实现红外弱小目标检测，不需要进行传统的背景预测。
Instead of traditional background prediction, this method detects infrared small and dim target by judging whether the local grey level surface possesses the two dimension Gauss function feature.
针对CCD光电序列探测图像中的弱小运动目标检测问题，提出了一种运动星空背景下的基于变换域特征的弱小目标检测算法。
For the dim point moving target detection of the CCD photoelectric image sequences, a new algorithm based on transform domain feature is proposed.
它的方法与单帧图像的检测是有很大区别的，所以可以说这是弱小目标检测算法中的两个不同的问题，所对应的算法也是不一样的。
So sequential images detection and single image detection are two different problems of small target detection algorithm which should be with corresponding algorithms.
仿真实验结果表明，该算法具有较高的检测率和良好的实时特性，能有效地检测出低信比红外图像序列中的弱小运动目标。
Simulations of real IR image sequence with low SNR prove the algorithm can effectively detect dim moving target, and has high detection probability and excellent real time performance.
提出一种有效的背景杂波预测形态神经网络模型，用于检测图像数据中的弱小目标。
An effective morphological neural network of background clutter prediction for detecting dim small targets in image data was proposed.
实验结果表明，该算法不但能够准确的检测出弱小目标的位置，还具有更快的速度，对于实时性检测，有很好的效果。
The experimental results indicate that the algorithm not only can detect accurately weak and small targets, but also have higher speed.
提出了一种弱小目标的管线检测算法。
A novel pipeline detection algorithm for dim target was presented.
提出了一种弱小目标的管线检测算法。
A novel pipeline detection algorithm for dim target was presented.
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