共查询到20条相似文献,搜索用时 93 毫秒
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Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. Based on human visual attention mechanisms, an automatic detection algorithm for infrared dim target is presented. After analyzing the characteristics of infrared dim target images, the method firstly designs Difference of Gaussians (DoG) filters to compute the saliency map. Then the salient regions where the potential targets exist in are extracted by searching through the saliency map with a control mechanism of winner-take-all (WTA) competition and inhibition-of-return (IOR). At last, these regions are identified by the characteristics of the dim IR targets, so the true targets are detected, and the spurious objects are rejected. The experiments are performed for some real-life IR images, and the results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection. 相似文献
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一种背景自适应调整的弱点目标探测算法 总被引:9,自引:7,他引:9
针对因复杂背景导致低信噪比的弱点目标探测率降低的问题,首先分析了从红外图像中探测弱点目标时,由于复杂和缓变背景下潜在目标探测率不同,而导致目标探测率降低的理论依据;并在该分析的基础上,提出了一种基于背景自适应调整的红外点目标探测算法。该方法利用鲁宾逊(Robinson)保护滤波器从经过预处理的图像中提取潜在目标;通过复杂背景模糊隶属度函数将图像映射到模糊特征平面,并由该特征平面计算背景调整因子,以对提取的潜在目标进行加权调整,从而降低了复杂背景的影响。实验结果表明,该算法可以显著提高复杂背景下红外点目标的检测概率,并且能够探测出信噪比为1的目标。 相似文献
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基于光流直方图的云背景下低帧频小目标探测方法 总被引:3,自引:2,他引:1
对低帧频、云层背景下,低信噪比的弱点目标探测率降低的问题.提出了光流直方图(OFH)的定义.并且给出了OFH的性质.分析了低帧频下红外图像探测弱点目标时探测率降低的原凶,提出了一种基于OFH背景补偿的红外点目标探测算法.利用OFH得到背景的运动欠量.进行运动背景补偿;然后利用目标与云层运动差异性,得到帧间比较结果,并对比较结果通过Robinson滤波器进一步滤除残留的边缘,达到降低虚警的目的.实验结果表明,该算法中以显著提高往复杂背景下红外点目标检测概率,并凡能够探测出信噪比为1的目标. 相似文献
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Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, two new algorithms – background estimate and frame difference fusion method, and building background with neighborhood mean method are presented. The basic principles and the implementing procedure of these algorithms for target detection are described. Using these algorithms, the experiments on some real-life IR images are performed. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective view and objective view. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection. 相似文献
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将人工智能算法引入目标检测,空间红外弱小目标的检测也可归为模糊检测的二分类问题。依据空中红外弱小目标的探测模型,建立了信号电压比光谱模型,仿真分析表明电压比变化趋势与目标的速度、姿态和两机态势有关,可用以检测目标。采用动态特征构建理论,构建了红外弱小目标的双色比特征空间,基于该特征空间,优化最小二乘分类算法,用于从光谱信号层级检测目标。该方法不仅缩小了样本数据量,而且防止了高斯核函数参数选择引起的“过拟合”现象,既保证了分类精度,又使分类速率提高近1倍,为人工智能算法用于红外弱小目标检测提供了参考依据。 相似文献
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基于小波域扩散滤波的弱小目标检测 总被引:1,自引:0,他引:1
分析了基于小波变换进行弱小目标检测的基本思想,利用小波变换的多尺度多分辨率特性,结合小波变换系数的方向特性和扩散滤波扩散方向的可选择性,提出了基于小波域扩散滤波的弱小目标检测算法。采用该算法对不同尺度、不同方向的小波系数分别进行扩散滤波,取得了较好的效果。仿真试验结果表明:该算法能在Gaussian噪声背景和不均匀背景下实现对对比度为2%的微弱目标的检测。 相似文献
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This paper presents an algorithm for detecting and tracking dim moving target in IR image sequence with low SNR. The algorithm, which is designed based on the locality preserving projection, accepts tensors as inputs. The justification for the algorithm comes from the role of the generalized eigenvalue problem in providing an optimal embedding for the manifold. Not only does the proposed method inherit the attractive characteristics of the locality preserving projections in terms of exploiting the intrinsic manifold structure, it is also appealing in terms of significant reduction in both space complexity and time complexity. Experimental results on two IR image sequences demonstrate the effectiveness of the proposed algorithm. 相似文献
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为了解决复杂背景下小目标的识别,提高检测速度的问题,提出了一种改进的中值滤波方法.用其进行背景抑制,保护了图像细节,提高了处理的实时性.在分析小目标图像特点的基础上,提出了采用击中击不中变换对图像进行分割,达到探测目标的目的.仿真结果验证了该算法是一种实时有效,且易于实现的目标探测方法. 相似文献
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This work presents a new method based on gray characteristic analysis for infrared dim small target detection under complex backgrounds. Firstly, an improved detection window with eight directions and three layers is introduced to investigate the gray distribution characteristic of different structure in an infrared image. Secondly, we adopt a pretreatment process based on morphology filter and mean filter to reduce the running time and propose a detection rule on characteristic analysis for infrared targets. Meanwhile a new parameter optimization algorithm based on fuzzy control theory is employed so that the detection rule could be independent of the initial parameters. Finally, experimental results indicate that the proposed method can effectively detect the dim small targets and has better tracking performance. 相似文献
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A new infrared dim small target enhancement algorithm based on toggle contrast operator is proposed. Toggle contrast operator is modified and used to construct operators using the image features derived from dilation and erosion operators. Then, based on the constructed operators, the operators which could be used to estimate the clutter background of the original infrared dim small target image are proposed using the same strategy as the definition of opening. Finally, the infrared dim small target is well enhanced through subtracting the estimated background from the original image. Experimental results on infrared images with different types of targets verified that the proposed method could effectively enhance infrared dim small target, which would be very useful for infrared dim small target detection and tracking. 相似文献
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基于数学形态学的弱点状运动目标的检测 总被引:10,自引:0,他引:10
提出了一种新的基于数学形态学的红外图像序列中弱点状运动目标的非参数检测算法。采用数学形态学抑制背景杂波干扰和增强目标,用沿时间轴投影和二维空域搜索代替复杂的时空三维搜索形成组合帧,然后在每条可能的轨迹上将进行目标能量累加,实现了一种快速检测前跟踪(TBD)检测算法。仿真实验表明:在恒虚警概率条件下,该检测算法能高效地检测信噪比约为2的弱点状运动目标,检测性能对噪声分布不敏感,能精确地得到目标的即时位置和速度信息,适合于实时图像处理和目标探测,具有很高的实用价值。 相似文献
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提出一种基于分块速度域的迭代红外运动目标检测算法来解决传统算法计算量巨大这一难题.首先,采用二维最小均方差滤波器对红外序列图像进行滤波,获得包含弱小目标以及残差的红外序列图像.然后,通过在序列图像块的速度域上应用改进的迭代运动目标检测算法进行能量累积,从而将弱小目标的运动速度在速度域进行累积增强,达到检测弱小运动目标的目的.最后在解算出的速度值附近进行搜索,得到弱小目标运动的精确速度.利用此速度进行空域能量累积,得到叠加图像,在此图上进行目标检测.与传统方法相比较,几组实验结果显示,本文提出的方法大大缩短了检测的时间,而且本文方法的检测效果也较好. 相似文献
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To improve contrast between dim target region and background in infrared (IR) long-range surveillance, this paper proposes a fast image enhancement approach using saliency feature extraction based on multi-scale decomposition. Firstly, a smooth based multi-scale decomposition is designed and applied to original infrared image, generating sub-images with various frequency components at different decomposition levels. The dim target regions of sub-images are extracted by a local frequency-tuned based saliency feature detection method, secondly. With saliency maps created by saliency extraction using multi-scale local windows with different sizes, the sub-images are enhanced at different decomposition scales. Finally, the enhanced result is reconstructed by synthesizing the all sub-images with adjustable synthetic weights. Since salient areas are analyzed based on fast multi-scale image decomposition, IR image can be s enhanced with good contrast successfully and rapidly. Compared with other algorithms, the experimental results prove that the proposed method is robust and efficient for IR image enhancement. 相似文献
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