A novel morphological edge detector based on adaptive weighted morphological operators is presented. It judges image edge and direction by adaptive weighted morphological structuring elements （SEs）. If the edge dire...A novel morphological edge detector based on adaptive weighted morphological operators is presented. It judges image edge and direction by adaptive weighted morphological structuring elements （SEs）. If the edge direction exists, a big weight factor in SE is put; if it does not exist, a small weight factor in SE is put. Thus we can achieve an intensified edge detector. Experimental results prove that the new operator＇s performance dominates those of classical operators for images in edge detection, and obtains superbly detail edges.展开更多
在G ady A gam等人工作的基础上,结合结构元素和约束参数的选择,对调节形态学基本算子进行了一定的分析,得到了几个等价定义和一个颇有意义的结论.最后结合实例,比较了调节形态学与普通形态学对噪声图像处理的结果和性能.实验结果表明,...在G ady A gam等人工作的基础上,结合结构元素和约束参数的选择,对调节形态学基本算子进行了一定的分析,得到了几个等价定义和一个颇有意义的结论.最后结合实例,比较了调节形态学与普通形态学对噪声图像处理的结果和性能.实验结果表明,这种新形态学算子比经典形态学算子具有更好的噪声抑制能力.展开更多
Generalized morphological operator can generate less statistical bias in the output than classical morphological operator. Comprehensive utilization of spectral and spatial information of pixels, an endmember extracti...Generalized morphological operator can generate less statistical bias in the output than classical morphological operator. Comprehensive utilization of spectral and spatial information of pixels, an endmember extraction algorithm based on generalized morphology is proposed. For the limitations of morphological operator in the pixel arrangement rule and replacement criteria, the reference pixel is introduced. In order to avoid the cross substitution phenomenon at the boundary of different object categories in the image, an endmember is extracted by calculating the generalized opening-closing(GOC) operator which uses the modified energy function as a distance measure. The algorithm is verified by using simulated data and real data. Experimental results show that the proposed algorithm can extract endmember automatically without prior knowledge and achieve relatively high extraction accuracy.展开更多
基金This work was supported by the National Natural Science Foundation of China under Grants No.60372034 and 60672168.
文摘A novel morphological edge detector based on adaptive weighted morphological operators is presented. It judges image edge and direction by adaptive weighted morphological structuring elements （SEs）. If the edge direction exists, a big weight factor in SE is put; if it does not exist, a small weight factor in SE is put. Thus we can achieve an intensified edge detector. Experimental results prove that the new operator＇s performance dominates those of classical operators for images in edge detection, and obtains superbly detail edges.
基金supported by the National Natural Science Foundation of China(No.61275010)the PhD Programs Foundation of Ministry of Education of China(No.20132304110007)
文摘Generalized morphological operator can generate less statistical bias in the output than classical morphological operator. Comprehensive utilization of spectral and spatial information of pixels, an endmember extraction algorithm based on generalized morphology is proposed. For the limitations of morphological operator in the pixel arrangement rule and replacement criteria, the reference pixel is introduced. In order to avoid the cross substitution phenomenon at the boundary of different object categories in the image, an endmember is extracted by calculating the generalized opening-closing(GOC) operator which uses the modified energy function as a distance measure. The algorithm is verified by using simulated data and real data. Experimental results show that the proposed algorithm can extract endmember automatically without prior knowledge and achieve relatively high extraction accuracy.
