We discuss remote-sensing-image fusion based on a multi-band wavelet and RGB feature fusion method. The fused data can be used to monitor the dynamic evolution of mining induced subsidence. High resolution panchromati...We discuss remote-sensing-image fusion based on a multi-band wavelet and RGB feature fusion method. The fused data can be used to monitor the dynamic evolution of mining induced subsidence. High resolution panchromatic image data and multi-spectral image data were first decomposed with a multi-ary wavelet method. Then the high frequency components of the high resolution image were fused with the features from the R, G, B bands of the multi-spectral image to form a new high frequency component. Then the newly formed high frequency component and the low frequency component were inversely transformed using a multi-ary wavelet method. Finally, color images were formed from the newly formed R, G, B bands. In our experiment we used images with a resolution of 10 m (SPOT), and TM30 images, of the Huainan mining area. These images were fused with a trinary wavelet method. In addition, we used four indexes—entropy, average gradient, wavelet energy and spectral distortion—to assess the new method. The result indicates that this new method can improve the clarity and resolution of the images and also preserves the information from the original images. Using the fused images for monitoring mining induced subsidence achieves a good effect.展开更多
Different image processing algorithms have been evaluated in the context of geological mapping using Landsat TM data. False color composites, the principal component imagery, and IHS decorrelation stretching method fo...Different image processing algorithms have been evaluated in the context of geological mapping using Landsat TM data. False color composites, the principal component imagery, and IHS decorrelation stretching method for Landsat-5 TM data have been found useful for delineating the regional geological features, mainly to provide the maximum geological information of the studied area . The study testifies that using which image processing yields best results for geological mapping in arid and semiarid regions by preserving morphological and spectral information. Generally, the studied area can be divided into three main geological units: Basaltic intrusive rocks, Metamorphic with varying intensities and Sedimentary rocks.展开更多
This paper develops a wide-band multi-spectral space for color representationwith Aitken PCA algorithm. This novel mathematical space using the broad-band spectra matchingmethod aims at improving the accuracy of color...This paper develops a wide-band multi-spectral space for color representationwith Aitken PCA algorithm. This novel mathematical space using the broad-band spectra matchingmethod aims at improving the accuracy of color representation as well as reducing costs forprocessing and storing multi-spectral images. The results show that the space can present ourexperimental original spectral spaces (i. e. Munsell color matt and DIN-6164 color chips) with highefficiency, and that the spanning space with three eigenvectors can present the original space atmore than 98% CSCR, and when 5 eigenvectors are used it can cover almost the whole o-riginal spaces.展开更多
Clonal selection feature selection algorithm （CSFS） based on clonal selection algorithm （CSA）, a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-d...Clonal selection feature selection algorithm （CSFS） based on clonal selection algorithm （CSA）, a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-dimensional images, and has better performance than traditional feature selection algorithms with more computational costs. In this paper, a fast clonal selection feature selection algorithm （FCSFS） for hyperspectral imagery is proposed to improve the convergence rate by using Cauchy mutation instead of non-uniform mutation as the primary immune operator. Two experiments are performed to evaluate the performance of the proposed algorithm in comparison with CSFS using hyperspectral remote sensing imagery acquired by the pushbroom hyperspectral imager （PHI） and the airborne visible/infrared imaging spectrometer （AVlRIS）, respectively. Experimental results demonstrate that the FCSFS converges faster than CSFS, hence providing an effective new option for dimensionality reduction of hyperspectral remote sensing imagery.展开更多
基金Project 2003-38 supported by the Geological Investigation Item of Anhui Province
文摘We discuss remote-sensing-image fusion based on a multi-band wavelet and RGB feature fusion method. The fused data can be used to monitor the dynamic evolution of mining induced subsidence. High resolution panchromatic image data and multi-spectral image data were first decomposed with a multi-ary wavelet method. Then the high frequency components of the high resolution image were fused with the features from the R, G, B bands of the multi-spectral image to form a new high frequency component. Then the newly formed high frequency component and the low frequency component were inversely transformed using a multi-ary wavelet method. Finally, color images were formed from the newly formed R, G, B bands. In our experiment we used images with a resolution of 10 m (SPOT), and TM30 images, of the Huainan mining area. These images were fused with a trinary wavelet method. In addition, we used four indexes—entropy, average gradient, wavelet energy and spectral distortion—to assess the new method. The result indicates that this new method can improve the clarity and resolution of the images and also preserves the information from the original images. Using the fused images for monitoring mining induced subsidence achieves a good effect.
文摘Different image processing algorithms have been evaluated in the context of geological mapping using Landsat TM data. False color composites, the principal component imagery, and IHS decorrelation stretching method for Landsat-5 TM data have been found useful for delineating the regional geological features, mainly to provide the maximum geological information of the studied area . The study testifies that using which image processing yields best results for geological mapping in arid and semiarid regions by preserving morphological and spectral information. Generally, the studied area can be divided into three main geological units: Basaltic intrusive rocks, Metamorphic with varying intensities and Sedimentary rocks.
基金rojectsupportedbytheNationalNaturalScienceFoundationofChina (No .60 1 770 0 5) .
文摘This paper develops a wide-band multi-spectral space for color representationwith Aitken PCA algorithm. This novel mathematical space using the broad-band spectra matchingmethod aims at improving the accuracy of color representation as well as reducing costs forprocessing and storing multi-spectral images. The results show that the space can present ourexperimental original spectral spaces (i. e. Munsell color matt and DIN-6164 color chips) with highefficiency, and that the spanning space with three eigenvectors can present the original space atmore than 98% CSCR, and when 5 eigenvectors are used it can cover almost the whole o-riginal spaces.
基金Supported by the Major State Basic Research Development Program (973 Program) of China (No. 2009CB723905)the National High Technology Research and Development Program (863 Program) of China (Nos.2009AA12Z114, 2007AA12Z148, 2007AA12Z181)+2 种基金the National Natural Sci-ence Foundation of China(Nos. 40771139,40523005, 40721001)the Research Fund for the Doctoral Program of Higher Education of China(No.200804861058)the Foundation of National Laboratory of Pattern Recognition
文摘Clonal selection feature selection algorithm （CSFS） based on clonal selection algorithm （CSA）, a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-dimensional images, and has better performance than traditional feature selection algorithms with more computational costs. In this paper, a fast clonal selection feature selection algorithm （FCSFS） for hyperspectral imagery is proposed to improve the convergence rate by using Cauchy mutation instead of non-uniform mutation as the primary immune operator. Two experiments are performed to evaluate the performance of the proposed algorithm in comparison with CSFS using hyperspectral remote sensing imagery acquired by the pushbroom hyperspectral imager （PHI） and the airborne visible/infrared imaging spectrometer （AVlRIS）, respectively. Experimental results demonstrate that the FCSFS converges faster than CSFS, hence providing an effective new option for dimensionality reduction of hyperspectral remote sensing imagery.
