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optimal band selection
相关语句
  最佳波段选择
     Optimal Band Selection Methods of Hyperspectral Remote Sensing Data
     高光谱遥感数据最佳波段选择方法研究
短句来源
  “optimal band selection”译为未确定词的双语例句
     Optimal band selection and combination of multi-spectrum data is the key for image enhancement, it directly influences eye estimation and object information distilled.
     多光谱遥感数据的最佳波段选取与组合是遥感图像增强处理的关键部分,直接影响到图像的目视解译和研究对象的信息提取。
短句来源
     This paper makes a study of the fusion technique of high-resolution satellite and hyperspectral imagery. A model for hyperspectral data fusion based on OIF method of optimal band selection is put forward.
     高光谱图像数据与高空间全色波段数据进行融合处理,可以在大大改善融合后成象光谱图像空间解析特性的条件下,选择性保持满足应用需求的成象光谱图像的光谱物理特性和波形形态,为深入地研究提供更好的条件。
短句来源
  相似匹配句对
     Optimal Design of Gain-flattened EDFA in C Band
     C波段增益平坦掺铒光纤放大器的优化设计
短句来源
     Optimal Design of L-band Preamplifier with Cascade Structure
     L-波段级联结构掺Er光纤放大器的优化设计
短句来源
     It is the optimal pattern.
     这个结果如同自然界生态平衡一样,是相对最优的格局。
短句来源
     Optimal Band Selection Methods of Hyperspectral Remote Sensing Data
     高光谱遥感数据最佳波段选择方法研究
短句来源
     Band of Brothers
     兄弟连
短句来源
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the intrinsical relationships of the “entropy”methods on optimal bands selection in multispectral remote sensing data interpretation are analysed,and,limitations of using these methods in hyperspectral remote sensing data interpretation explained.The optimal bands selection principles and methods based on the classes distinguishability are put forward.The validity,accuracy,limitations and computational complexity of the processing methods concerned are illustrated through experiments.

分析了遥感图像解译中多光谱遥感数据选择最佳波段组合所用信息量诸方法的内在联系,说明了信息量方法用于高光谱遥感数据最佳波段选择的局限性,提出了基于类间可分性的最佳波段选择原则和方法.通过试验,说明了各种处理方法的有效性、局限性和计算复杂度

This paper proposes an approach to edge analysis of multi_band image using Marr's method,on the basis of the introductions of Marr theory and the principles of edge detection proposed by Marr and Hildreth. As to Marr theory,this paper describes its frame structure with a few words in order to let the readers have a whole concept to it. Then the principles of edge detection proposed by Marr_Hildreth is analyzed by dividing into two parts,which are how to select the smooth filter and why the Laplacian operator...

This paper proposes an approach to edge analysis of multi_band image using Marr's method,on the basis of the introductions of Marr theory and the principles of edge detection proposed by Marr and Hildreth. As to Marr theory,this paper describes its frame structure with a few words in order to let the readers have a whole concept to it. Then the principles of edge detection proposed by Marr_Hildreth is analyzed by dividing into two parts,which are how to select the smooth filter and why the Laplacian operator is valid. They show that after using the Gauss smooth filter,the edge of the image can be detected well with the Laplacian operator. LOG operator is the integration of the two parts. On this base,the paper emphasizes on exploring the valid approaches for multi_band remote sensing image(TM image). Some ways are pointed out in the paper,such as weighted vector summation,optimal band selection,etc. But the approach used in the experiments is dependent upon the number of “cross_point" using LOG operator for each band respectively. In details,we can use LOG operator to process every band image to get “cross_point" edge,and then use a detection method to select the gray of the final edge image,which can describe the best information of the multi_band image,namely how to decide the most appropriate edge gray,which comes from every band. The results of the experiments include the edge image of each band with different σ and the edge image of the multi_band image. The experiments using TM image show the better effect of multi_band image analysis.

简要介绍了Marr理论的基本框架 ,并详细介绍了Marr_Hildreth边缘检测理论的基本原理 ,同时给出了LOG模板算子实例。在此基础上 ,提出这一理论用于多波段影像边缘分析的几种不同的方法 ,指出了本文所采取方法的原理和算法流程。试验结果的分析对比说明 ,多波段影像分析的效果优于单波段

The intrinsical relationships of the “entropy” methods on optimal bands selection in multispectral remote sensing data interpretation are analysed,and limitations of using these methods in hyperspectral remote sensing data interpretation explained.The optimal bands selection principles and methods based on the classes distinguishability are put forward.The validity,accuracy,limitations and computational complexity of the processing methods concerned are illustrated throuh experiments.

分析了多光谱遥感数据最佳波段选择的联合熵、行列式值及最佳指数等信息量计算方法的内在联系 ,说明了信息量方法用于高光谱遥感数据最佳波段选择的局限性 ,提出了基于类间可分性的最佳波段选择原则和方法。通过试验 ,说明了各种处理方法的有效性、局限性和计算复杂度。

 
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