A background estimation technique was developed based on sequential image time stability for slowly changing background in real-time image processing.
针对背景的缓变特性和实时图像处理的需求，该文提出了一种基于序列图像时间稳定性特征的背景估计技术。
An approach of background estimation is presented using characters of random variable moments and applied in moving object detection under static background.
利用随机变量的各阶矩的性质，构造了一种基于高阶统计量的背景估计方法，并将其应用于静态背景下的运动目标检测。
On the basis of the characteristics of the IR images, an algorithm of background estimation based on grayscale morphology with multiple structuring elements is presented.
该文在分析红外图像统计特征的基础上，提出了一种基于多结构元素灰度形态学的红外背景估计算法。
Background estimation based on block is proposed to solve the problem of building background model and updating background which can enhance the robust of moving object detection.
针对静态背景下的背景差法，通过研究如何得到、以及如何及时更新背景模型，增强运动目标检测随环境变化的鲁棒性，提出了多级分块的背景估计方法。
Firstly, a background estimation method based on small window and two dimension median filter is presented after detail analysis of the model of small infrared target, noise and clutter.
首先分析了红外小目标、噪声及其杂波特性，提出了用小窗口的二维中值滤波进行背景估计；
This paper researches the application of morphology reconstruction algorithm in dim point target detection and tracing, mainly in background estimation and post processing stage after detection.
重点研究了形态学重构算法在微弱目标检测和跟踪中的应用，主要体现在对原始图像的背景估计过程和检测后处理过程。
Traditional methods of signal detection and estimation were based on the assumption that the background noise is white.
传统的信号检测和估计方法一般是建立在背景噪声是白噪声这一假设基础之上。
On this basis, combined with one sort of background updating model, vehicle tracking algorithm is presented through using two-dimension motion estimation technique in dynamic image processing.
在此基础上，使用动态图像处理技术中的二维运动估计技术，结合背景更新模型提出了一种车辆跟踪算法。
White noise deconvolution or input white noise estimation problem has important application background in oil seismic exploration.
白噪声反卷积或输入白噪声估计问题在石油地震勘探中有重要的应用背景。
The object of global motion estimation module is to calculate the relative motion vector of adjacent frames' background, that is, the global motion vector.
帧间全局运动估计模块的设计目标是计算相邻帧的背景的相对运动的矢量，这一矢量被称为全局运动矢量。
Change detection, mapping parameter estimation, moving objects and background detection are used to implement image motion segmentation.
通过变化检测，映射参数估算，运动区域和背景检测来实现运动分割。
Blind image restoration has a strong background of mathematics, including estimation theory, ill-posed problem solution method, linear algebra, stochastic process, numerical analysis, and so on.
图像盲复原具有很强的数学背景，同估计理论、病态逆问题求解理论、线性代数、随机过程和数值分析等都有着密切的联系。
In the thesis, the algorithm of background subtracting, frame difference algorithm, motion estimation based on optical flow field and object tracking based on active shape contour are investigated.
本文研究了背景相减算法、差分法、基于光流场的运动估计和基于主动形状模型的目标跟踪算法。
At the beginning of this thesis, the background and significance of research on the theory of least uncertainty estimation are stated and the content of the research is introduced.
本文首先论述了最小不确定度估计理论的研究背景和研究意义，简要介绍了该估计理论的研究内容。
This system can realize the detection of the non-rigid moving object and the estimation of the background velocity through the Level-Set method and piece-wise smooth motion field constraint.
该系统采用水平集方法，利用分段平滑运动场的约束条件，实现非刚体运动目标检测和背景的运动估算。
The fast integer pixel motion estimation algorithm for video sequences which are smooth, vary slowly and have many background blocks is discussed.
首先讨论了针对运动量较小的、包含有大量背景块的视频序列的快速运动估计算法，包括整像素和半像素快速算法。
The background samples are chosen by thresholding inter-frame differences, and the Gaussian kernel density estimation is used to estimate the probability density function of background intensity.
通过相隔固定的帧差值阅值化得到背景样本值，并采用高斯核密度估计方法计算背景灰度的概率密度函数。
Under this background, we try to review recent progress in study on acoustic vector sensor signal processing, such as signal detection, DOA estimation, beamforming, and so on.
在此背景下，本文尝试综述声矢量传感器信号处理研究的当前进展，如信号检测、DOA估计、波束形成等。
We use Bayesian maximum a posteriori estimation training a speaker model from background model, to solve the problem of model miss matching in speaker verification system.
采用贝叶斯最大后验概率估计的方式，从统一背景模型中生成说话人模型。
Firstly, we introduce the research situation of the local polynomial regression estimation and its basic concept from the model's background.
首先，从产生背景入手，介绍了非参数局部多项式回归估计模型的基本概念以及研究概况。
The parameter estimation of sine-wave flooded in strong noise background is an important and practical technique, and it is the base theory of spectrum analysis estimation.
估计淹没在噪声中的正弦波参量是具有实际应用价值和普遍意义的技术之一，也是测试所有谱估计性能的基础。
Simluation results show that the maximum entropy spectral estimation and LMS adaptive algorithm can extract echo signal of laser ranging system effectively from background noises.
仿真分析表明，最大熵谱估计和LMS自适应算法相结合可以有效地从背景噪声中提取有用的激光反射回波信号。
According to different existences of noise background and signals, there are several approaches to azimuth Angle estimation based on a single vector hydrophone.
根据不同的噪声背景和信号形式，单矢量水听器有多种方位估计方法。
In this article, performance of estimation of signal parameters in PAssive Synthetic Array (PASA) is studied, focusing on the background of airborne platform intercepting narrowband microwave signals.
针对利用机载运动平台对窄带微波信号进行侦测的背景，研究了被动虚拟阵列(PASA)对窄带微波信号的参数估计性能。
From this point, the algorithm is implemented by searching and constructing a background image efficiently. With regard to global motion models, four-parameter estimation model is adopted.
算法从全局运动估计的基础出发，利用背景宏块运动相似性的特点快速建立背景宏块集合并采用常用的四参数全局运动估计模型估计运动参数。
A simple strategy named 3 frames difference background subtraction is adopted to detect moving object, and movement estimation and compensation are combined to improve processing speed.
采用简单的三帧差背景剪除策略检测运动目标，合并运动估计和背景补偿以加快系统反应速度。
Technically, a practical and stable system for the estimation of the background AD exposure parameter prediction is brought up.
从技术角度提出实现背景广告曝光参数虚拟预测的一个切实可行的体系结构。
Base on this characteristic, this paper presents a passive image forgery detection algorithm which uses blind estimation of background noise.
本文利用这一特点，提出了一种基于背景噪声分析的图像真伪被动鉴别算法。
Base on this characteristic, this paper presents a passive image forgery detection algorithm which uses blind estimation of background noise.
本文利用这一特点，提出了一种基于背景噪声分析的图像真伪被动鉴别算法。
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