Due to the data acquired by most optical earth observation satellite such as IKONOS, QuickBird-2 and GF-1 consist of a panchromatic image with high spatial resolution and multiple multispectral images with low spatial...Due to the data acquired by most optical earth observation satellite such as IKONOS, QuickBird-2 and GF-1 consist of a panchromatic image with high spatial resolution and multiple multispectral images with low spatial resolution. Many image fusion techniques have been developed to produce high resolution multispectral image. Considering panchromatic image and multispectral images contain the same spatial information with different accuracy, using the least square theory could estimate optimal spatial information. Compared with previous spatial details injection mode, this mode is more accurate and robust. In this paper, an image fusion method using Bidimensional Empirical Mode Decomposition (BEMD) and the least square theory is proposed to merge multispectral images and panchromatic image. After multi-spectral images were transformed from RGB space into IHS space, next I component and Panchromatic are decomposed by BEMD, then using the least squares theory to evaluate optimal spatial information and inject spatial information, finally completing fusion through inverse BEMD and inverse intensity-hue-saturation transform. Two data sets are used to evaluate the proposed fusion method, GF-1 images and QuickBird-2 images. The fusion images were evaluated visually and statistically. The evaluation results show the method proposed in this paper achieves the best performance compared with the conventional method.展开更多
Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark...Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.展开更多
In the process of cutting,the relative vibration between the cutter and the workpiece has an important effect on the surface topography.In this study,the bidimensional empirical mode decomposition(BEMD)method is used ...In the process of cutting,the relative vibration between the cutter and the workpiece has an important effect on the surface topography.In this study,the bidimensional empirical mode decomposition(BEMD)method is used to identify such effect.According to Riesz transform theory,a type of isotropic monogenic signal is proposed.The boundary data is extended on the basis of a similarity principle that deals with serious boundary effect problem.The decomposition examples show that the improved BEMD can effectively solve the problem of boundary effect and decompose the original machined surface topography at multiple scales.The characteristic surface topography representing the relative vibration between the cutter and the workpiece through feature identification is selected.In addition,the spatial spectrum analysis of the extracted profile is carried out.The decimal part of the frequency ratio that has an important effect on the shape of the contour can be accurately identified through contour extraction and spatial spectrum analysis.The decomposition results of simulation and experimental surface morphology demonstrate the validity of the improved BEMD algorithm in realizing the relative vibration identification between the cutter and the workpiece.展开更多
In order to improve the quality of remote sensing image fusion,a new method combining nonsubsampled Laplacian pyramid (NLP)and bidimensional empirical mode decomposition(BEMD)is proposed.First,the high resolution panc...In order to improve the quality of remote sensing image fusion,a new method combining nonsubsampled Laplacian pyramid (NLP)and bidimensional empirical mode decomposition(BEMD)is proposed.First,the high resolution panchromatic image (PAN)is decomposed using NLP until the approximate component and the low resolution multispectral image(MS)contain features with a similar scale.Then,the approximation component and the MS are decomposed by BEMD,resulting in a number of bidimensional intrinsic mode functions(BIMF)and a residue respectively.The instantaneous frequency is computed in 4 directions of the BIMFs.Considering the positive or negative coefficients in the corresponding position,a weighted algorithm is designed for fusing the high frequency details using the instantaneous frequency and the coefficient absolute value of the BIMFs as fusion feature.The fused image is then obtained through inverse BEMD and NLP.Experimental results have illustrated the advantage of this method over the IHS,DWT andà-Trous wavelet in both spectral and spatial detail qualities.展开更多
文摘Due to the data acquired by most optical earth observation satellite such as IKONOS, QuickBird-2 and GF-1 consist of a panchromatic image with high spatial resolution and multiple multispectral images with low spatial resolution. Many image fusion techniques have been developed to produce high resolution multispectral image. Considering panchromatic image and multispectral images contain the same spatial information with different accuracy, using the least square theory could estimate optimal spatial information. Compared with previous spatial details injection mode, this mode is more accurate and robust. In this paper, an image fusion method using Bidimensional Empirical Mode Decomposition (BEMD) and the least square theory is proposed to merge multispectral images and panchromatic image. After multi-spectral images were transformed from RGB space into IHS space, next I component and Panchromatic are decomposed by BEMD, then using the least squares theory to evaluate optimal spatial information and inject spatial information, finally completing fusion through inverse BEMD and inverse intensity-hue-saturation transform. Two data sets are used to evaluate the proposed fusion method, GF-1 images and QuickBird-2 images. The fusion images were evaluated visually and statistically. The evaluation results show the method proposed in this paper achieves the best performance compared with the conventional method.
基金The National Science and Technology Support Project under contract No.2014BAB12B02the Natural Science Foundation of Liaoning Province under contract No.201602042
文摘Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.
基金This work was supported by the Science Challenge Project(Grant No.JCKY2016212A506-0105)the National Natural Science Foundation of China(Grant No.11802279).
文摘In the process of cutting,the relative vibration between the cutter and the workpiece has an important effect on the surface topography.In this study,the bidimensional empirical mode decomposition(BEMD)method is used to identify such effect.According to Riesz transform theory,a type of isotropic monogenic signal is proposed.The boundary data is extended on the basis of a similarity principle that deals with serious boundary effect problem.The decomposition examples show that the improved BEMD can effectively solve the problem of boundary effect and decompose the original machined surface topography at multiple scales.The characteristic surface topography representing the relative vibration between the cutter and the workpiece through feature identification is selected.In addition,the spatial spectrum analysis of the extracted profile is carried out.The decimal part of the frequency ratio that has an important effect on the shape of the contour can be accurately identified through contour extraction and spatial spectrum analysis.The decomposition results of simulation and experimental surface morphology demonstrate the validity of the improved BEMD algorithm in realizing the relative vibration identification between the cutter and the workpiece.
基金supported by the National Basic Research Program ofChina("973"Program)(Grant Nos.2006CB701300,2006CB701304)the China Postdoctoral Foundation(Grant No.2007041172),Hubei Natural Science Foundation(Grant No.2007ABA042)LIESMARS Special Research Fund and the Wuhan Key Scientific and Technological Project(Grant No.200810321144)
文摘In order to improve the quality of remote sensing image fusion,a new method combining nonsubsampled Laplacian pyramid (NLP)and bidimensional empirical mode decomposition(BEMD)is proposed.First,the high resolution panchromatic image (PAN)is decomposed using NLP until the approximate component and the low resolution multispectral image(MS)contain features with a similar scale.Then,the approximation component and the MS are decomposed by BEMD,resulting in a number of bidimensional intrinsic mode functions(BIMF)and a residue respectively.The instantaneous frequency is computed in 4 directions of the BIMFs.Considering the positive or negative coefficients in the corresponding position,a weighted algorithm is designed for fusing the high frequency details using the instantaneous frequency and the coefficient absolute value of the BIMFs as fusion feature.The fused image is then obtained through inverse BEMD and NLP.Experimental results have illustrated the advantage of this method over the IHS,DWT andà-Trous wavelet in both spectral and spatial detail qualities.
