Because of cloudy and rainy weather in south China, optical remote sens-ing images often can＇t be obtained easily. With the regional trial results in Baoying, Jiangsu province, this paper explored the fusion model an...Because of cloudy and rainy weather in south China, optical remote sens-ing images often can＇t be obtained easily. With the regional trial results in Baoying, Jiangsu province, this paper explored the fusion model and effect of ENVISAT/SAR and HJ-1A satel ite multispectral remote sensing images. Based on the ARSIS strat-egy, using the wavelet transform and the Interaction between the Band Structure Model （IBSM）, the research progressed the ENVISAT satel ite SAR and the HJ-1A satel ite CCD images wavelet decomposition, and low/high frequency coefficient re-construction, and obtained the fusion images through the inverse wavelet transform. In the light of low and high-frequency images have different characteristics in differ-ent areas, different fusion rules which can enhance the integration process of self-adaptive were taken, with comparisons with the PCA transformation, IHS transfor-mation and other traditional methods by subjective and the corresponding quantita-tive evaluation. Furthermore, the research extracted the bands and NDVI values around the fusion with GPS samples, analyzed and explained the fusion effect. The results showed that the spectral distortion of wavelet fusion, IHS transform, PCA transform images was 0.101 6, 0.326 1 and 1.277 2, respectively and entropy was 14.701 5, 11.899 3 and 13.229 3, respectively, the wavelet fusion is the highest. The method of wavelet maintained good spectral capability, and visual effects while improved the spatial resolution, the information interpretation effect was much better than other two methods.展开更多
This paper describes a new type of transformed Landsat images (LBV images) and their application in discriminating soil gleization in subtropic region of China. LBV transformation was worked out by the present author ...This paper describes a new type of transformed Landsat images (LBV images) and their application in discriminating soil gleization in subtropic region of China. LBV transformation was worked out by the present author for extracting useful information from original landsat images. Using this method three black and white images, L image, B image and V image, were computer generated from original bands of a Landsat scene, which covers a.large area of 34 528 km2 in Hubei and Hunan provinces in south China. Then a color composite was produced by these three images. This kind of black-and-white and color images contained rich and definite geographic information. By a field work, the relationship between the colors on the composite and the land use/cover categories on the ground was established. 37 composite colors and 70 ground feature categories can be discriminated altogether. Finally, 17 land use/cover categories and 10 subregions suffering from soil gleization were determined, and the gleization area for the study area was estimated to be 731.3 km2.展开更多
A Landsat data transformation method which was proposed by the author was applied to extract useful information from data of 769 ground feature classification units of worldwide scope.Three most important characterist...A Landsat data transformation method which was proposed by the author was applied to extract useful information from data of 769 ground feature classification units of worldwide scope.Three most important characteristic values--the general radiance level L,the visible-infrared radiation balance B and the band radiance variation vector (direction and speed) V were calculated.Then the 769 class units were sorted into 106 groups based on their natural characteristics.The means and standard deviations of L,B and V values for all the groups were calculated.The distributions of the 106 groups or the 769 units on the number axes of L,B and V,in the planes of L-B,L-V and B-V,and in the space of L-B-V were investigated.Finally,the typical numerical characteristics of the various ground features are discussed in consideration of their worldwide variations in the present paper.展开更多
A simple spectral preserving image fusion technique, Edge Enhancement Color Normalized (EECN), was proposed to merge two kinds of image data. In addition, a mathematical model was also proposed to evaluate spectral pr...A simple spectral preserving image fusion technique, Edge Enhancement Color Normalized (EECN), was proposed to merge two kinds of image data. In addition, a mathematical model was also proposed to evaluate spectral property of the fused production of EECN. The results were clearly demonstrated by an image fusion experiment using Landsat-5 TM and IRS-1C Panchromatic images of Beijing, China. The visual evaluation and mathematical analysis compared with Brovey transform confirmed that the fused image of EECN is quite similar in color to the lower resolution multi-spectral images, and its space resolution is the same as the higher solution panchromatic image.展开更多
This paper calculates the parameters of image position and orientation,proposes a mathematical model and adopts a new method with three steps of transformations based on parallel ray projection.Every step of the model...This paper calculates the parameters of image position and orientation,proposes a mathematical model and adopts a new method with three steps of transformations based on parallel ray projection.Every step of the model is strict,and the map function of each transformation is the first order polynomials and other simple function.The final calculation of the parameters is for the linear equations with good status.As a result,the problem of the relativity of image parameter calculation is solved completely.Some experiments are carried out.展开更多
Due to the large quantities of data and high relativity of the spectra of remote sensing images, K-L transformation is used to eliminate the relativity. An improved ISODATA(Interative Self-Organizing Data Analysis Tec...Due to the large quantities of data and high relativity of the spectra of remote sensing images, K-L transformation is used to eliminate the relativity. An improved ISODATA(Interative Self-Organizing Data Analysis Technique A) algorithm is used to extract the spectrum features of the images. The computation is greatly reduced and the dynamic arguments are realized. The comparison of features between two images is carried out, and good results are achieved in simulation.展开更多
On the basis of a thorough understanding of the physical characteristics of remote sensing image, this paper employs the theories of wavelet transform and signal sampling to develop a new image fusion algorithm. The a...On the basis of a thorough understanding of the physical characteristics of remote sensing image, this paper employs the theories of wavelet transform and signal sampling to develop a new image fusion algorithm. The algorithm has been successfully applied to the image fusion of SPOT PAN and TM of Guangdong province, China. The experimental results show that a perfect image fusion can be built up by using the image analytical solution and re-construction in the image frequency domain based on the physical characteristics of the image formation. The method has demonstrated that the results of the image fusion do not change spectral characteristics of the original image.展开更多
Content-based satellite image registration is a difficult issue in the fields of remote sensing and image processing. The difficulty is more significant in the case of matching multisource remote sensing images which ...Content-based satellite image registration is a difficult issue in the fields of remote sensing and image processing. The difficulty is more significant in the case of matching multisource remote sensing images which suffer from illumination, rotation, and source differences. The scale-invariant feature transform （SIFT） algorithm has been used successfully in satellite image registration problems. Also, many researchers have applied a local SIFT descriptor to improve the image retrieval process. Despite its robustness, this algorithm has some difficulties with the quality and quantity of the extracted local feature points in multisource remote sensing. Furthermore, high dimensionality of the local features extracted by SIFT results in time-consuming computational processes alongside high storage requirements for saving the relevant information, which are important factors in content-based image retrieval （CBIR） applications. In this paper, a novel method is introduced to transform the local SIFT features to global features for multisource remote sensing. The quality and quantity of SIFT local features have been enhanced by applying contrast equalization on images in a pre-processing stage. Considering the local features of each image in the reference database as a separate class, linear discriminant analysis （LDA） is used to transform the local features to global features while reducing di- mensionality of the feature space. This will also significantly reduce the computational time and storage required. Applying the trained kernel on verification data and mapping them showed a successful retrieval rate of 91.67% for test feature points.展开更多
基金supported by the National Natural Science Foundation of China(41171336)the Project of Jiangsu Province Agricultural Science and Technology Innovation Fund(CX12-3054)
文摘Because of cloudy and rainy weather in south China, optical remote sens-ing images often can＇t be obtained easily. With the regional trial results in Baoying, Jiangsu province, this paper explored the fusion model and effect of ENVISAT/SAR and HJ-1A satel ite multispectral remote sensing images. Based on the ARSIS strat-egy, using the wavelet transform and the Interaction between the Band Structure Model （IBSM）, the research progressed the ENVISAT satel ite SAR and the HJ-1A satel ite CCD images wavelet decomposition, and low/high frequency coefficient re-construction, and obtained the fusion images through the inverse wavelet transform. In the light of low and high-frequency images have different characteristics in differ-ent areas, different fusion rules which can enhance the integration process of self-adaptive were taken, with comparisons with the PCA transformation, IHS transfor-mation and other traditional methods by subjective and the corresponding quantita-tive evaluation. Furthermore, the research extracted the bands and NDVI values around the fusion with GPS samples, analyzed and explained the fusion effect. The results showed that the spectral distortion of wavelet fusion, IHS transform, PCA transform images was 0.101 6, 0.326 1 and 1.277 2, respectively and entropy was 14.701 5, 11.899 3 and 13.229 3, respectively, the wavelet fusion is the highest. The method of wavelet maintained good spectral capability, and visual effects while improved the spatial resolution, the information interpretation effect was much better than other two methods.
文摘This paper describes a new type of transformed Landsat images (LBV images) and their application in discriminating soil gleization in subtropic region of China. LBV transformation was worked out by the present author for extracting useful information from original landsat images. Using this method three black and white images, L image, B image and V image, were computer generated from original bands of a Landsat scene, which covers a.large area of 34 528 km2 in Hubei and Hunan provinces in south China. Then a color composite was produced by these three images. This kind of black-and-white and color images contained rich and definite geographic information. By a field work, the relationship between the colors on the composite and the land use/cover categories on the ground was established. 37 composite colors and 70 ground feature categories can be discriminated altogether. Finally, 17 land use/cover categories and 10 subregions suffering from soil gleization were determined, and the gleization area for the study area was estimated to be 731.3 km2.
文摘A Landsat data transformation method which was proposed by the author was applied to extract useful information from data of 769 ground feature classification units of worldwide scope.Three most important characteristic values--the general radiance level L,the visible-infrared radiation balance B and the band radiance variation vector (direction and speed) V were calculated.Then the 769 class units were sorted into 106 groups based on their natural characteristics.The means and standard deviations of L,B and V values for all the groups were calculated.The distributions of the 106 groups or the 769 units on the number axes of L,B and V,in the planes of L-B,L-V and B-V,and in the space of L-B-V were investigated.Finally,the typical numerical characteristics of the various ground features are discussed in consideration of their worldwide variations in the present paper.
文摘A simple spectral preserving image fusion technique, Edge Enhancement Color Normalized (EECN), was proposed to merge two kinds of image data. In addition, a mathematical model was also proposed to evaluate spectral property of the fused production of EECN. The results were clearly demonstrated by an image fusion experiment using Landsat-5 TM and IRS-1C Panchromatic images of Beijing, China. The visual evaluation and mathematical analysis compared with Brovey transform confirmed that the fused image of EECN is quite similar in color to the lower resolution multi-spectral images, and its space resolution is the same as the higher solution panchromatic image.
文摘This paper calculates the parameters of image position and orientation,proposes a mathematical model and adopts a new method with three steps of transformations based on parallel ray projection.Every step of the model is strict,and the map function of each transformation is the first order polynomials and other simple function.The final calculation of the parameters is for the linear equations with good status.As a result,the problem of the relativity of image parameter calculation is solved completely.Some experiments are carried out.
文摘Due to the large quantities of data and high relativity of the spectra of remote sensing images, K-L transformation is used to eliminate the relativity. An improved ISODATA(Interative Self-Organizing Data Analysis Technique A) algorithm is used to extract the spectrum features of the images. The computation is greatly reduced and the dynamic arguments are realized. The comparison of features between two images is carried out, and good results are achieved in simulation.
基金ProjectsupportedbytheNationalNaturalScienceFoundationofChina (No .40 0 2 30 0 4 ) .
文摘On the basis of a thorough understanding of the physical characteristics of remote sensing image, this paper employs the theories of wavelet transform and signal sampling to develop a new image fusion algorithm. The algorithm has been successfully applied to the image fusion of SPOT PAN and TM of Guangdong province, China. The experimental results show that a perfect image fusion can be built up by using the image analytical solution and re-construction in the image frequency domain based on the physical characteristics of the image formation. The method has demonstrated that the results of the image fusion do not change spectral characteristics of the original image.
文摘Content-based satellite image registration is a difficult issue in the fields of remote sensing and image processing. The difficulty is more significant in the case of matching multisource remote sensing images which suffer from illumination, rotation, and source differences. The scale-invariant feature transform （SIFT） algorithm has been used successfully in satellite image registration problems. Also, many researchers have applied a local SIFT descriptor to improve the image retrieval process. Despite its robustness, this algorithm has some difficulties with the quality and quantity of the extracted local feature points in multisource remote sensing. Furthermore, high dimensionality of the local features extracted by SIFT results in time-consuming computational processes alongside high storage requirements for saving the relevant information, which are important factors in content-based image retrieval （CBIR） applications. In this paper, a novel method is introduced to transform the local SIFT features to global features for multisource remote sensing. The quality and quantity of SIFT local features have been enhanced by applying contrast equalization on images in a pre-processing stage. Considering the local features of each image in the reference database as a separate class, linear discriminant analysis （LDA） is used to transform the local features to global features while reducing di- mensionality of the feature space. This will also significantly reduce the computational time and storage required. Applying the trained kernel on verification data and mapping them showed a successful retrieval rate of 91.67% for test feature points.
