景物边缘信息是进行图象分析和识别的重要属性，如何有效地从噪声图象中提取边缘是这些领域中的难点。
Edge is an important attribute for image analysis and recognition, but it is difficult to effectively extract edge from noisy image in the domain.
本文通过对景观空间、景物序列、组景手法分析，营造一个和谐景观艺术空间形态，形成景观设计特有的空间语言。
This article builds a space situation of harmony attractions art and forms its special space language through analyzing on at - traction space object order and the way of making attraction.
然后对低频子带进行多重分形特性分析，再将多重分形谱作为特征参量进行像素筛选，筛选出标志不同景物的像素点。
Then, multifractal analysis is performed for low frequency sub-band. The multifractal spectrum is used as the characteristic parameters to filter pixels which mark different scenery.
景物的深度信息对于图象分析是很重要的。
用功率谱的方法对任意景物在空间频域进行分析表明，功率谱对于自然景物具有一定的不变性。
Different scenes are analyzed in the power spectrum spatial frequency domain, it can be shown that the power spectrum of most natural scenes is of invariability.
分析和量化了输入景物噪声对联合变换相关器性能的影响。
The effect of noise in the input scene on the performance of the joint transform correlator is analyzed and quantified.
并通过分析《序曲》和《在海湾》的景物描写，揭示出隐藏在她作品背后浓浓的乡愁。
Based on a detailed analysis of her description of nature in Prelude and at the Bay, the paper has suggested that an overtone of homesickness be sensed in her lines.
论文结合大量的景物形态的设计实例，从单体和整体两方面对住区环境景物形态进行归类与分析，并对各项具体设计提出相应的策略。
This dissertation according to a host of actual examples, generalizing and analyzing the form of artifacts in two aspects, individual and integral form, putting forward some advices.
通过详细介绍了长沙市潇湘大道的道路照明设计与附属绿化景物的泛光设计，分析与总结出了城市干道的照明设计经验。
The paper introduces the development of green lights firstly, and then it analyses the actualities of road illumination on the basis of Chongqing citys correlative data.
首次在有限视场的输入景物下通过移动刀刃法对扫描成像过程中垂直扫描方向系统像方MTF的检测进行了分析和模拟计算。
Under the input scenery with finite visual field, the analyses and simulative calculation of the image side OTF of vertical direction of the scanning image by moving blade have been done firstly.
现在对于纹理图像的分析和分类广泛用于瑕疵定位、景物识别、图像检索、遥感图像分析等多个领域。
Nowadays, texture image analysis and classification is widely used in blemish locate, object recognize, image search, remote sensing image analysis and other fields.
现在对于纹理图像的分析和分类广泛用于瑕疵定位、景物识别、图像检索、遥感图像分析等多个领域。
Nowadays, texture image analysis and classification is widely used in blemish locate, object recognize, image search, remote sensing image analysis and other fields.
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