红外监视告警系统中的复杂背景抑制算法研究
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摘要
红外监视告警系统是依靠被动地接受目标红外辐射实现对目标的探测、识别和跟踪的光电信息装备,因此具有隐蔽性好、角分辨率高和抗电磁干扰能力强等优点,它已成了现代信息对抗系统中的一个重要组成部分,受到了各国军方的普遍重视。因此,如何最大限度地提高其对红外目标的探测能力,尽可能在远距离外获取来袭目标相关信息,对提高信息对抗系统的性能具有重要意义。但由于目标距离较远时,它在红外像机的成像面上尺寸较小,只有几个到几十个像素,无形状和纹理信息,并且几乎淹没在复杂背景之中,信杂比很低。因此,如何有效地抑制红外弱小目标图像的复杂背景是检测出弱小目标的前提,它是一项具有重要理论意义和工程应用价值的前沿技术研究课题。
本论文在对现有红外图像背景抑制技术进行全面综合深入分析的基础上,针对多种场景下红外图像中目标和背景具有的不同辐射强度及其分布结构的特点,对复杂背景抑制技术进行了深入的研究,并充分利用多尺度几何分析、局部滤波、统计学与变分偏微分方程等理论工具,研究并提出了多种各具特色的背景抑制算法,取得的主要研究成果如下:
(1)利用非下采样轮廓波变换所具有的多尺度、多方向和平移不变性的诸多特点和采用特征值选择截断和模糊非线性抑制算子对分解后的子带系数值实施调整的技术途径,研究出了分别基于奇异值分解和模糊逻辑的两种红外图像弱小目标背景抑制新算法。实验结果表明该两种新算法不仅都能很好地抑制云层起伏这类复杂背景,而且还能保存并增强目标信号。
(2)通过分析图像中每个像素点与其周围像素点在空间距离、灰度值和局部邻域上的关系,设计并实现了两种基于多分辨率双边滤波和多尺度非局部均值滤波的红外图像弱小目标背景抑制新算法,实验证明,其可有效地抑制地势起伏和地面路网这两类杂波背景,并保存和增强了目标强度信息。
(3)将贝叶斯最大后验估计与剪切波变换相结合,设计并实现了一种更有效的基于剪切波变换高斯尺度混合模型的红外图像弱小目标背景抑制新算法,实验结果显示新算法能有效抑制地空探测系统中可能出现的地面人工建筑物这类复杂红外背景。
(4)利用变分偏微分方程理论中能量泛函和多尺度分析表达概念,设计了基于RX算子改进的各向异性非线性扩散方程和全变差-Gabor模型两种背景抑制算法,完成对地空探测系统中可能出现的地面人工建筑物等复杂背景的抑制。不仅仿真结果验证了其正确性和有效性。而且已将全变差-Gabor模型算法成功地应用于基于凝视型成像的红外监视告警系统中。
Infrared Surveillance Warning System (ISWS) is electro-optical information equipment which detect, recognise and track targets by receiving their infrared emission passively. The ISWS which has invisibility, high resolving ability and fine anti-amming ability. For these advantages, ISWS beomes an important component of the modern information warfare system, and obtains wide attention and energetic cooperation in recent years by militarys. Therefore, how to make the best of infrared target detection ability to increase the distance of target detection and obtain the related information, have become important significance to improve the performance of information warfare system. However, because of target along distance, there are small size, only serveral pixels and no shape, texture information in imaging plane for infrared camera and targets are submerged in complex background. Therefore, comparing with other topics in the field of infrared target detection and tracking, how complex backgrounds can be robustly suppressed under low signal-to-clutter ratio have becomes frontier research topics which have important theory significance and engineering application value.
In this paper, based on comprehensive analysis for in-the-art infrared image background suppression technique and considering different emission intensity and distributed structure in infrared image between dim small target and background, complex background suppression techniques are used research deeper for key pre-processing technique of dim and small target detection and tracking. Multi-scale geometry analysis, local filter, statistics and variational partial differential equation theorys are analyzed and used, respectively, and then a seris of new infrared image dim and small target background suppresion algorithms are provided:
(1)According to nonsubsampled contourlet transform (NSCT) characteristics with multi-scale, multi-directional and translation invariance. Develop two new infrared image dim and small target background suppression algorithms based on singularity value decomposition and fuzzy logic which adjusted the NSCT subbands coefficients with truncated eigenvalue and fuzzy nonlinear background suppression operator, respectively. The experimental results demonstrate that new algorithms can suppress the background of clouds fluctuating effectively, save and enhance target signal.
(2)Analyze relationship each pixel with local neighbourhood pixel in spatial distances, intensity and local regions. Design and implement two new infrared image dim and small target background suppression algorithms based on multiresolution bilateral filter and multi-scale non-local means filter. The experimental results demonstrate that new algorithms can suppress the background of terrain fluctuating and ground road network effectively, save and enhance target intensity information.
(3)Combing Bayesian maximum a posteriori estimation with shearlet transform. Design and implement a new dim and small target background suppression algorithm based on the Gaussian scale mixture model creatively. The experimental results demonstrate that the new algorithm can suppress complex background of artificial building for surface-sky detection system effectively.
(4)Analyze the common algorithms of variational partial differential equation. According to characteristic with energy functional and multi-scale analysis. Construct and implement dim and small target background suppression algorithms based on RX operator improved anisotropic nonlinear diffusion equation and total variation Gabor model for artificial building of surface-sky detection system background suppression and keep the target signal steadily. Several experiments testify theirs practicability and validity. And then, total variation Gabor model algorithm is applied in ISWS with staring detector successfully.
本论文在对现有红外图像背景抑制技术进行全面综合深入分析的基础上,针对多种场景下红外图像中目标和背景具有的不同辐射强度及其分布结构的特点,对复杂背景抑制技术进行了深入的研究,并充分利用多尺度几何分析、局部滤波、统计学与变分偏微分方程等理论工具,研究并提出了多种各具特色的背景抑制算法,取得的主要研究成果如下:
(1)利用非下采样轮廓波变换所具有的多尺度、多方向和平移不变性的诸多特点和采用特征值选择截断和模糊非线性抑制算子对分解后的子带系数值实施调整的技术途径,研究出了分别基于奇异值分解和模糊逻辑的两种红外图像弱小目标背景抑制新算法。实验结果表明该两种新算法不仅都能很好地抑制云层起伏这类复杂背景,而且还能保存并增强目标信号。
(2)通过分析图像中每个像素点与其周围像素点在空间距离、灰度值和局部邻域上的关系,设计并实现了两种基于多分辨率双边滤波和多尺度非局部均值滤波的红外图像弱小目标背景抑制新算法,实验证明,其可有效地抑制地势起伏和地面路网这两类杂波背景,并保存和增强了目标强度信息。
(3)将贝叶斯最大后验估计与剪切波变换相结合,设计并实现了一种更有效的基于剪切波变换高斯尺度混合模型的红外图像弱小目标背景抑制新算法,实验结果显示新算法能有效抑制地空探测系统中可能出现的地面人工建筑物这类复杂红外背景。
(4)利用变分偏微分方程理论中能量泛函和多尺度分析表达概念,设计了基于RX算子改进的各向异性非线性扩散方程和全变差-Gabor模型两种背景抑制算法,完成对地空探测系统中可能出现的地面人工建筑物等复杂背景的抑制。不仅仿真结果验证了其正确性和有效性。而且已将全变差-Gabor模型算法成功地应用于基于凝视型成像的红外监视告警系统中。
Infrared Surveillance Warning System (ISWS) is electro-optical information equipment which detect, recognise and track targets by receiving their infrared emission passively. The ISWS which has invisibility, high resolving ability and fine anti-amming ability. For these advantages, ISWS beomes an important component of the modern information warfare system, and obtains wide attention and energetic cooperation in recent years by militarys. Therefore, how to make the best of infrared target detection ability to increase the distance of target detection and obtain the related information, have become important significance to improve the performance of information warfare system. However, because of target along distance, there are small size, only serveral pixels and no shape, texture information in imaging plane for infrared camera and targets are submerged in complex background. Therefore, comparing with other topics in the field of infrared target detection and tracking, how complex backgrounds can be robustly suppressed under low signal-to-clutter ratio have becomes frontier research topics which have important theory significance and engineering application value.
In this paper, based on comprehensive analysis for in-the-art infrared image background suppression technique and considering different emission intensity and distributed structure in infrared image between dim small target and background, complex background suppression techniques are used research deeper for key pre-processing technique of dim and small target detection and tracking. Multi-scale geometry analysis, local filter, statistics and variational partial differential equation theorys are analyzed and used, respectively, and then a seris of new infrared image dim and small target background suppresion algorithms are provided:
(1)According to nonsubsampled contourlet transform (NSCT) characteristics with multi-scale, multi-directional and translation invariance. Develop two new infrared image dim and small target background suppression algorithms based on singularity value decomposition and fuzzy logic which adjusted the NSCT subbands coefficients with truncated eigenvalue and fuzzy nonlinear background suppression operator, respectively. The experimental results demonstrate that new algorithms can suppress the background of clouds fluctuating effectively, save and enhance target signal.
(2)Analyze relationship each pixel with local neighbourhood pixel in spatial distances, intensity and local regions. Design and implement two new infrared image dim and small target background suppression algorithms based on multiresolution bilateral filter and multi-scale non-local means filter. The experimental results demonstrate that new algorithms can suppress the background of terrain fluctuating and ground road network effectively, save and enhance target intensity information.
(3)Combing Bayesian maximum a posteriori estimation with shearlet transform. Design and implement a new dim and small target background suppression algorithm based on the Gaussian scale mixture model creatively. The experimental results demonstrate that the new algorithm can suppress complex background of artificial building for surface-sky detection system effectively.
(4)Analyze the common algorithms of variational partial differential equation. According to characteristic with energy functional and multi-scale analysis. Construct and implement dim and small target background suppression algorithms based on RX operator improved anisotropic nonlinear diffusion equation and total variation Gabor model for artificial building of surface-sky detection system background suppression and keep the target signal steadily. Several experiments testify theirs practicability and validity. And then, total variation Gabor model algorithm is applied in ISWS with staring detector successfully.
引文
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