In this paper, three techniques, line run coding, quadtree DF (Depth-First) representation and H coding for compressing classified satellite cloud images with no distortion are presented. In these three codings, the f...In this paper, three techniques, line run coding, quadtree DF (Depth-First) representation and H coding for compressing classified satellite cloud images with no distortion are presented. In these three codings, the first two were invented by other persons and the third one, by ourselves. As a result, the comparison among their compression rates is. given at the end of this paper. Further application of these image compression technique to satellite data and other meteorological data looks promising.展开更多
To overcome the problem of insufficient expression of fine texture when gradient mode is used as an image feature extraction operator in traditional PM model,which leads to excessive diffusion in these fine texture re...To overcome the problem of insufficient expression of fine texture when gradient mode is used as an image feature extraction operator in traditional PM model,which leads to excessive diffusion in these fine texture regions and texture ambiguity,this paper proposes ANRDPM(Anti-noise and Reverse Diffusion PM model)noise reduction model based on the new anti-noise coefficient and reverse diffusion concept.In this model,the meter gradient operator is used as the image feature extractor to solve the shortage of the traditional gradient operator in the ability to express details.Secondly,a new anti-noise coefficient based on Gaussian curvature and noise intensity is proposed to solve the problem that the meter gradient operator is allergic to large noise points.In addition,a reverse diffusion filter based on a local variance of residuals is introduced to enhance the smoothed texture information in the image.Finally,the new model is discretized by a finite difference algorithm,and simulation results show that the proposed ANRDPM model not only performs well in smoothing image noise,but also effectively protects image texture information and structural integrity.展开更多
Nature has shown us that the microstructure of the skin of fast-swimming sharks in the ocean can reduce the skin friction drag due to the well-known shark-skin effect.In the present study,the effect of shark-skin-insp...Nature has shown us that the microstructure of the skin of fast-swimming sharks in the ocean can reduce the skin friction drag due to the well-known shark-skin effect.In the present study,the effect of shark-skin-inspired riblets on coherent vortex structures in a turbulent boundary layer（TBL） is investigated.This is done by means of tomographic particle image velocimetry（TPIV） measurements in channel fl ws over an acrylic plate of drag-reducing riblets at a friction Reynolds number of 190.The turbulent fl ws over drag-reducing riblets are verifie by a planar time-resolved particle image velocimetry（TRPIV） system initially,and then the TPIV measurements are performed.Two-dimensional（2D） experimental results with a dragreduction rate of around 4.81% are clearly visible over triangle riblets with a peak-to-peak spacing s＋of 14,indicating from the drag-reducing performance that the buffer layer within the TBL has thickened;the logarithmic law region has shifted upward and the Reynolds shear stress decreased.A comparison of the spatial topological distributions of the spanwise vorticity of coherent vortex structures extracted at different wall-normal heights through the improved quadrant splitting method shows that riblets weaken the amplitudesof the spanwise vorticity when ejection（Q2） and sweep（Q4） events occur at the near wall,having the greatest effect on Q4 events in particular.The so-called quadrupole statistical model for coherent structures in the whole TBL is verified Meanwhile,their spatial conditional-averaged topological shapes and the spatial scales of quadrupole coherent vortex structures as a whole in the overlying turbulent fl w over riblets are changed,suggesting that the riblets dampen the momentum and energy exchange between the regions of near-wall and outer portion of the TBL by depressing the bursting events（Q2 and Q4）,thereby reducing the skin friction drag.展开更多
Objectives:When detecting changes in synthetic aperture radar(SAR)images,the quality of the difference map has an important impact on the detection results,and the speckle noise in the image interferes with the extrac...Objectives:When detecting changes in synthetic aperture radar(SAR)images,the quality of the difference map has an important impact on the detection results,and the speckle noise in the image interferes with the extraction of change information.In order to improve the detection accuracy of SAR image change detection and improve the quality of the difference map,this paper proposes a method that combines the popular deep neural network with the clustering algorithm.Methods:Firstly,the SAR image with speckle noise was constructed,and the FFDNet architecture was used to retrain the SAR image,and the network parameters with better effect on speckle noise suppression were obtained.Then the log ratio operator is generated by using the reconstructed image output from the network.Finally,K-means and FCM clustering algorithms are used to analyze the difference images,and the binary map of change detection results is generated.Results:The experimental results have high detection accuracy on Bern and Sulzberger’s real data,which proves the effectiveness of the method.展开更多
文摘In this paper, three techniques, line run coding, quadtree DF (Depth-First) representation and H coding for compressing classified satellite cloud images with no distortion are presented. In these three codings, the first two were invented by other persons and the third one, by ourselves. As a result, the comparison among their compression rates is. given at the end of this paper. Further application of these image compression technique to satellite data and other meteorological data looks promising.
基金funded by National Nature Science Foundation of China,grant number 61302188.
文摘To overcome the problem of insufficient expression of fine texture when gradient mode is used as an image feature extraction operator in traditional PM model,which leads to excessive diffusion in these fine texture regions and texture ambiguity,this paper proposes ANRDPM(Anti-noise and Reverse Diffusion PM model)noise reduction model based on the new anti-noise coefficient and reverse diffusion concept.In this model,the meter gradient operator is used as the image feature extractor to solve the shortage of the traditional gradient operator in the ability to express details.Secondly,a new anti-noise coefficient based on Gaussian curvature and noise intensity is proposed to solve the problem that the meter gradient operator is allergic to large noise points.In addition,a reverse diffusion filter based on a local variance of residuals is introduced to enhance the smoothed texture information in the image.Finally,the new model is discretized by a finite difference algorithm,and simulation results show that the proposed ANRDPM model not only performs well in smoothing image noise,but also effectively protects image texture information and structural integrity.
基金supported by the National Natural Science Foundation of China (Grants 11332006,11272233,and 11411130150)the foundation from the China Scholarship Council (CSC) (Grant 201306250092)the Foundation Project for Outstanding Doctoral Dissertations of Tianjin University
文摘Nature has shown us that the microstructure of the skin of fast-swimming sharks in the ocean can reduce the skin friction drag due to the well-known shark-skin effect.In the present study,the effect of shark-skin-inspired riblets on coherent vortex structures in a turbulent boundary layer（TBL） is investigated.This is done by means of tomographic particle image velocimetry（TPIV） measurements in channel fl ws over an acrylic plate of drag-reducing riblets at a friction Reynolds number of 190.The turbulent fl ws over drag-reducing riblets are verifie by a planar time-resolved particle image velocimetry（TRPIV） system initially,and then the TPIV measurements are performed.Two-dimensional（2D） experimental results with a dragreduction rate of around 4.81% are clearly visible over triangle riblets with a peak-to-peak spacing s＋of 14,indicating from the drag-reducing performance that the buffer layer within the TBL has thickened;the logarithmic law region has shifted upward and the Reynolds shear stress decreased.A comparison of the spatial topological distributions of the spanwise vorticity of coherent vortex structures extracted at different wall-normal heights through the improved quadrant splitting method shows that riblets weaken the amplitudesof the spanwise vorticity when ejection（Q2） and sweep（Q4） events occur at the near wall,having the greatest effect on Q4 events in particular.The so-called quadrupole statistical model for coherent structures in the whole TBL is verified Meanwhile,their spatial conditional-averaged topological shapes and the spatial scales of quadrupole coherent vortex structures as a whole in the overlying turbulent fl w over riblets are changed,suggesting that the riblets dampen the momentum and energy exchange between the regions of near-wall and outer portion of the TBL by depressing the bursting events（Q2 and Q4）,thereby reducing the skin friction drag.
文摘Objectives:When detecting changes in synthetic aperture radar(SAR)images,the quality of the difference map has an important impact on the detection results,and the speckle noise in the image interferes with the extraction of change information.In order to improve the detection accuracy of SAR image change detection and improve the quality of the difference map,this paper proposes a method that combines the popular deep neural network with the clustering algorithm.Methods:Firstly,the SAR image with speckle noise was constructed,and the FFDNet architecture was used to retrain the SAR image,and the network parameters with better effect on speckle noise suppression were obtained.Then the log ratio operator is generated by using the reconstructed image output from the network.Finally,K-means and FCM clustering algorithms are used to analyze the difference images,and the binary map of change detection results is generated.Results:The experimental results have high detection accuracy on Bern and Sulzberger’s real data,which proves the effectiveness of the method.
