共查询到19条相似文献,搜索用时 109 毫秒
1.
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
2.
基于时空非局部相似性的海上红外弱小目标检测 总被引:1,自引:0,他引:1
《光子学报》2018,(11)
为了消除海上红外弱小目标检测中图像背景杂波和噪声的影响,提出了一种基于时空非局部相似性的红外图像弱小目标检测方法.该方法充分利用了相邻帧的红外图像序列间海面背景图像块的非局部自相关特性以及每帧内非局部背景图像块间的相似特性,并引入时空域图像块模型,该模型可利用加速近端梯度方法来有效求解.实验结果表明,与传统的红外弱小目标检测方法相比,所提方法不仅能更有效地保留目标的特征信息,还能使红外图像的峰值信噪比提高1.2倍以上,信杂比提高1.8倍以上. 相似文献
3.
4.
《光学学报》2010,(6)
针对复杂天空背景条件下低信噪比的红外弱小目标检测问题,提出了一种基于对称差分和光流估计相结合的目标检测算法。对序列红外图像做对称差分运算,通过图像差减运算和自适应阈值分割提取目标可能的运动区域,并对区域做扩张和叠加处理,得到连续帧间目标可能出现的区域。计算每个区域红外图像的光流场,对光流场进行阈值分割,辅以数学形态学滤波等方法,检测区域中的目标。该算法充分利用对称差分运算计算量小和光流检测准确度高的特点,在保证检测准确度的同时大大减少了目标检测算法的计算量。实验及结果分析表明,基于对称差分和光流估计的目标检测算法能实时有效地检测出复杂天空背景下的红外弱小目标。 相似文献
5.
6.
7.
提出了基于频域映射与多尺度Top-Hat变换的红外弱小目标检测算法。通过分割经典Top-Hat的单一结构元素,获得多尺度膨胀结构元素,对红外弱小目标进行增强,有效抑制杂波与噪声背景;基于Butterworth低通滤波与截止频率,构建Butterworth差异带通滤波,联合Fourier变换,建立粗显著性检测机制,通过提取其幅度与相位频谱,基于2D高斯平滑滤波,定义细显著性检测机制,在频域中凸显弱小目标,并将红外目标的空间与强度相关性作为识别标准,精确定位候选目标;根据红外目标运动与虚警的速度差异特征,定义弱小目标连续帧速度模型,在帧间充分抑制候选区域中的虚假目标,检测出完整的弱小目标。实验结果显示:与当前红外弱小目标检测技术相比,面对复杂背景干扰,提出的算法具有更高的检测精度,可精确定位出完整的弱小目标,呈现出更好的ROC特性曲线。 相似文献
8.
9.
10.
11.
红外弱小目标检测是安防监控、侦察探测、精确制导等领域的关键技术。为了提高复杂背景条件下红外弱小目标检测的准确性和实时性,提出了一种基于深度学习的红外弱小目标检测算法YOLO-FCSP。根据红外图像中弱小目标的特点,在YOLO检测框架的基础上,通过减少下采样次数,结合跨阶段局部模块、Focus结构和空间金字塔池化结构设计了特征提取网络。借鉴多路径聚合的思路优化特征融合网络,同时调整检测输出层数量,通过信息复用提高特征利用效率。实验结果表明,本文提出的算法在检测红外弱小目标时具有较高的准确率和检测速度,精度和召回率分别为91.9%和94.6%,平均准确率(AP)值达到92.6%,检测速度达到170 f/s,满足实际应用中实时检测的需求。 相似文献
12.
为了有效抑制复杂背景的干扰,降低复杂背景所带来的虚警,提高目标检测的信噪比,提出了一种基于复滤波器组的红外弱小目标检测算法。分析了复杂背景下带有弱小目标的红外图像中复杂背景和弱小目标图像各自的频谱特性,并引入了分频段处理的思想。比较了各种滤波器的性能,并选用了基于复小波的滤波器组,用该滤波器组将红外弱小目标图像分解到各个子频域;对分解后的各频段图像分别进行基于罗宾逊滤波的目标检测处理,提取各频段图像中的奇异点;根据目标图像和背景图像的频谱特性的定量分析结果,选取合适的权值,将各频段检测的结果进行加权融合,得到最终的处理效果。实验结果表明:弱小目标检测方法较之于传统的不分频段的高通滤波处理方式可以获得更高的信噪比,目标得到明显的增强,背景杂波得到更有效的抑制,各项探测指标均更优。 相似文献
13.
14.
A hybrid moving target detection approach in multi-resolution framework for thermal infrared imagery is presented. Background subtraction and optical flow methods are widely used to detect moving targets. However, each method has some pros and cons which limits the performance. Conventional background subtraction is affected by dynamic noise and partial extraction of targets. Fast independent component analysis based background subtraction is efficient for target detection in infrared image sequences; however the noise increases for small targets. Well known motion detection method is optical flow. Still the method produces partial detection for low textured images and also computationally expensive due to gradient calculation for each pixel location. The synergistic approach of conventional background subtraction, fast independent component analysis and optical flow methods at different resolutions provide promising detection of targets with reduced time complexity. The dynamic background noise is compensated by the background update. The methodology is validated with benchmark infrared image datasets as well as experimentally generated infrared image sequences of moving targets in the field under various conditions of varying illumination, ambience temperature and the distance of the target from the sensor location. The significant value of F-measure validates the efficiency of the proposed methodology with high confidence of detection and low false alarms. 相似文献
15.
16.
Wang D.Wang M. 《应用光学》2017,(1):106-113
Aiming at solving accuracy problem of infrared small target detection in sky and ocean background scenarios of infrared image sequences, a novel infrared small target detection based on multi-filters algorithm fusion method is presented in this paper. Firstly infrared small target and imaging, time and space characteristics of the corresponding background noise are analyzed. Tophat algorithm with improved Robinson guard filter are then integrated to highlight target and suppress clutter background by using infrared small target imaging features. Adaptive threshold segmentation is used to extract candidate targets, while Unger smoothing filter and multi-objects association filter are used to eliminate random noise and false targets in the candidate targets. Multiple experiments of infrared small target image sequences are implemented, and experimental results show that proposed method can detect infrared small targets at 99% detection rate with high reliability and good real-time performance. © 2017, Editorial Board, Journal of Applied Optics. All right reserved. 相似文献
17.
18.
We apply graph matching method to detect infrared small moving targets using image sequences. Candidates (interest points) detected in the first frame form one graph and the same candidates in the last frame form another one. The real moving targets are extracted by matching these two graphs. Experimental results demonstrate that the proposed method is robust and efficient to the translation and rotation of the background. 相似文献
19.
Delian Liu Jianqi Zhang Weike Dong 《International Journal of Infrared and Millimeter Waves》2007,28(5):373-381
A new algorithm is presented which deals with the problem of detecting small moving targets in infrared image sequences that
also contain drifting and evolving clutter. Through development of models of the temporal behavior of the static background,
target and cloud edge on a single pixel basis, the new algorithm employing the connecting line of the stagnation points (CLSP)
of the temporal profile as the baseline is created and tested. The deviation of the temporal profile and its CLSP is analyzed
and it is determined that the distribution of the residual temporal profile obtained by subtracting the baseline from the
temporal profile can be modeled by a Gaussian distribution. The occurrences of the targets have intensity values significantly
different to the distribution of the residual temporal profile. Unlike the conventional 3-D method, this new algorithm operates
on the temporal profile in 1-D space, not in 3-D space, thus having a higher computational efficiency. Experiments with real
IR image sequences have proved the validity of the new approach.
This work was supported by National Natural Science Fund of China (No. 60277005). 相似文献