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top hat相关的网络例句

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与 top hat 相关的网络例句 [注:此内容来源于网络,仅供参考]

A new small target detection method based on energy accumulation and morphology top-hat operator is presented for solving detection of moving small target with low SNR in infrared image sequence.

针对红外序列图象中运动弱小目标的检测问题,提出了一种基于能量累积与Top Hat算子的小目标检测方法。

In this paper, an increasing sequence of structure element was used to detect the best response to each pixel of image and the output of the response pixel would be the most sensitive structure element by using this improved Top-Hat transform.

通过定义一个递增的结构元素序列对图像进行Top-Hat变换,在每一个像素处用不同的结构元素作Top-Hat变换,以寻找对该像素最敏感的结构元素,并把此结构元素对图像的处理结果作为该像素处最后的输出值。

Moreover, the differences between the classical and the new Top-hat transformations, and the properties of the new Top-hat transformation are analyzed.

接着分析了新型Top-hat变换和经典Top-hat变换的不同,并详细分析了由此产生的新特性。

Optimized design of morphological improved top-hat filter based on improved genetic algorithms.

基于改进遗传算法优化的形态学修正TOP-HAT滤波器设计方法。

Detection of the crack skeletonImage pre-processing technologies are firstly used to eliminate noise and enhance the image, such as Top-Hat transform.

裂缝的骨架提取本文首先对裂缝图像进行了预处理,采用了形态学的Top-Hat变化等方法对图像进行了噪声去除和图像的增强。

The article offerred the morphology Top-Hat operator that a kind of genetic algorithm optimizes on foundation of traditional morphology functor.

本文在传统形态学算子基础上提出了一种遗传算法优化的形态学Top-Hat算子。

This paper proposed an improved algorithm of Top-hat transform based on graunulometry. Top-Hat transform can extract lighter objects and structures in gray image.

数学形态学中的Top-Hat变换是一种提取图像中局部较亮的目标或信息的技术。

After analyzing traditional image difference subtraction algorithm, based on the theory of mathematical morphology, Top-Hat operation algorithm is chosen to remove image noise and perform the task of object detection based on gray morphology theory.

在分析传统的差影减法实现目标检测算法的的基础上,基于灰度数学形态学原理,采用 Top-Hat运算去除图像噪声并完成纸病图像的可疑目标的快速检测。

Then, the new Top-hat transformation is proposed through regrouping the calculation of the classical Top-hat transformation by using two different but related structuring elements.

首先分析了经典Top-hat变换的缺点,然后用两个不同但互相关联的结构元素重新组织经典Top-hat变换的运算形成新型Top-hat变换。

To improve the detectability of the Top-hat transformation and suppress the effect of noises or clutters, a new class of Top-hat transformation is proposed. Firstly, the shortcomings of the classical Top-hat transformation are analyzed.

为了简单有效地提高Top-hat变换的目标检测能力,降低噪声及复杂背景对其性能的影响,提出了一类新的Top-hat变换。

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