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  “边缘质量”译为未确定词的双语例句
     There are mainly 3 factors causing obvious decrease of the quality of virtual edge: chromatic dispersion, high-frequency noises ane problems caused by CCD pixels in critical state.
     使虚边缘质量有明显下降的主要因素有3个:光的色散、高频噪声和CCD光敏元处于临界状态所带来的问题。
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     Quality.
     质量
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     Edge
     边缘
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     QUALITY
     质量
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     Control Sidewall Effect to Improve the Sinter Output and Quality
     抑制边缘效应提高烧结矿产量和质量
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     PEOPLE ON THE EDGE
     人在边缘
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  edge quality
In this paper we discuss our investigations on the effect of two types of laser writing techniques, namely front- and rear-side laser writing, with regard to the feature size and the edge quality of a feature.
      
It is proved conclusively that for the patterning of masks, front-side laser writing is a better technique than rear-side laser writing with regard to smaller feature size and better edge quality.
      
Edge quality can be discriminated, but is not recognised in unfamiliar orientations.
      
The optimum cut edge quality is as rectangular and as burr-free as possible.
      
The test series show, that oscillation can have an effect on the tensile strength, friction and work hardening of sheet metal and as a result on the cutting force and the cut edge quality.
      
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This paper extensively discusses the procedure for vector quantization based on Ko-honen self organizing feature map and uses a relative new version of frequency sensitive technology. The most important feature of it is to use a laplas operator to detect the image edge and induct the neural network to learn more information about the high frequency area in order to diminish block effects and therefore reconstruct the image with higher fidelity. The experiment results prove the effectiveness of this new approch....

This paper extensively discusses the procedure for vector quantization based on Ko-honen self organizing feature map and uses a relative new version of frequency sensitive technology. The most important feature of it is to use a laplas operator to detect the image edge and induct the neural network to learn more information about the high frequency area in order to diminish block effects and therefore reconstruct the image with higher fidelity. The experiment results prove the effectiveness of this new approch.

矢量量化是一种重要的数据压缩方法.本文利用Kohonen自组织映射神经网络进行矢量量化,首次较为详细地讨论了具体实现的步骤与细节,并在此基础上为改善边缘质量,提出一种基于Laplas算子检测边缘弓引导神经网络训练的方法,并通过实验证明其效果是明显的.

Recently the vector quantization(VQ) has received considerable interests as a powerful image data compression technique.However,studies of image coding with VQ have revealed that VQ for image compression suffers from edge degradation in the reproduced images.In this paper,we describe an adaptive learning method of the edge preserving VQ based on kohonen′s self orfganizing feature map neural network.The learning procedure is performed by extracting the edge of the whole image,then adaptively adjusting the learning...

Recently the vector quantization(VQ) has received considerable interests as a powerful image data compression technique.However,studies of image coding with VQ have revealed that VQ for image compression suffers from edge degradation in the reproduced images.In this paper,we describe an adaptive learning method of the edge preserving VQ based on kohonen′s self orfganizing feature map neural network.The learning procedure is performed by extracting the edge of the whole image,then adaptively adjusting the learning rate that are determined according to the subimage block "activity factor",which represent the sensitivity of the block feature to the human visual system.Compared with direct image VQ coding,the experiment results show the reproduced images quality are well improved,at the same compression ratio.

矢量量化(VQ)作为一种有效的图像数据压缩技术,越来越受到人们的重视,但研究表明:目前矢量量化技术存在的主要问题之一是图像边缘失真严重.本文讨论了一种应用神经网络的图像边缘保持矢量量化方法,它以Kohonen的自组织特征映射算法(SOFM)为基础,根据人的视觉系统对图像边缘的敏感性,在图像编码前,先对整幅图像的边缘提取,再将每一图像子块的边缘特性用一“活跃因子”表示.在矢量量化过程中,根据不同训练矢量(图像子块)的活跃因子,自适应地调整SOFM的学习参数.实验结果表明,和单纯用神经网络直接进行矢量量化相比较,应用这种技术的图像编码在同一压缩比下译码图像的边缘质量有明显的提高.

In order to obtain true edges from noisy image,three steps are introduced. Firstly contour bougie morphological filtering is adopted with leaving a very little noise that is amalgamated with or close to true image edges. Secondly canny method that is less likely to be “fooled" by noise is applied. Finally LCS(least cost searching) method is used to improve edges' quality by removing false edges which are caused by left noise.

为很好地检测出被噪声污染的图像的边缘 ,首先采用CB形态滤波对图像进行预处理 ,再用canny法获得较高的边缘检出率 ,最后采用最小费用搜索法进一步提高了边缘质量 .建立在结构元素轮廓的概念之上 ,以集合延展度为特征进行处理的CB形态滤波保证了滤除噪声的同时保持图像细节 ,canny算法对噪声和弱边缘有更强的适应性 ,而最小费用搜索法对因滤波后遗留噪声引起的虚假边缘有很好的抑制能力 .实例表明这种检测方法能够获得较好的图像边缘 .

 
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