Ghost imaging(GI)is thought of as a promising imaging method in many areas.However,the main drawback of GI is the huge measurement data and low signal-to-noise ratio.In this paper,we propose a novel mask-based denoisi...Ghost imaging(GI)is thought of as a promising imaging method in many areas.However,the main drawback of GI is the huge measurement data and low signal-to-noise ratio.In this paper,we propose a novel mask-based denoising scheme to improve the reconstruction quality of GI.We first design a mask through the maximum between-class variance(OTSU)method and construct the measurement matrix with speckle patterns.Then,the correlated noise in GI can be effectively suppressed by employing the mask.From the simulation and experimental results,we can conclude that our method has the ability to improve the imaging quality compared with traditional GI method.展开更多
Fengyun-4 A(FY-4 A) belongs to the second generation of geostationary meteorological satellite series in China. Its observations with high frequency and resolution provide a better data basis for monitoring of extreme...Fengyun-4 A(FY-4 A) belongs to the second generation of geostationary meteorological satellite series in China. Its observations with high frequency and resolution provide a better data basis for monitoring of extreme weather such as sudden flood disasters. In this study, the flood disasters occurred in Bangladesh, India, and some other areas of South Asia in August 2018 were investigated by using a rapid multi-temporal synthesis approach for the first time for removal of thick clouds in FY-4 A images. The maximum between-class variance algorithm(OTSU;developed by Otsu in 2007) and linear spectral unmixing methods are used to extract the water area of flood disasters. The accuracy verification shows that the water area of flood disasters extracted from FY-4 A is highly correlated with that from the high-resolution satellite datasets Gaofen-1(GF-1) and Sentinel-1 A, with the square correlation coefficient R2 reaching 0.9966. The average extraction accuracy of FY-4 A is over 90%. With the rapid multi-temporal synthesis approach used in flood disaster monitoring with FY-4 A satellite data, advantages of the wide coverage, fast acquisition,and strong timeliness with geostationary meteorological satellites are effectively combined. Through the synthesis of multi-temporal images of the flood water body, the influence of clouds is effectively eliminated, which is of great significance for the real-time flood monitoring. This also provides an important service guarantee for the disaster prevention and reduction as well as economic and social development in China and the Asia-Pacific region.展开更多
This paper proposes an automatic method of pore combination recognition,which is an important feature to hardwood recognition.After extracting edge from wood microscopic cross-section, based on area histogram of the s...This paper proposes an automatic method of pore combination recognition,which is an important feature to hardwood recognition.After extracting edge from wood microscopic cross-section, based on area histogram of the similar circle regions,the method classifies all regions into two classes with maximum between-class variance,so as to distinguish the pore from other textures,which are similar in shapes but different in sizes.Meanwhile, second objective function about average area of closed regions is used to improve the pore segmentation performance.At last,the method uses adjacency degree of pore set to judge pore combination.The experiments demonstrate that the task of pore segmentation can be completed successfully for all kinds of pore distribution and combination,and also the correct combinations of pores are given.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.61627823)the Foundation for Excellent Young Talents of Jilin Province,China(Grant No.20190103010JH)+2 种基金the “13th Five-Year” Science and Technology Research Project of the Education Department of Jilin Province,China(Grant No.JJKH20190277KJ)the China Postdoctoral Science Foundation(Grant No.2018M641759)the Fundamental Research Funds for the Central Universities,China(Grant No.2412018QD002)
文摘Ghost imaging(GI)is thought of as a promising imaging method in many areas.However,the main drawback of GI is the huge measurement data and low signal-to-noise ratio.In this paper,we propose a novel mask-based denoising scheme to improve the reconstruction quality of GI.We first design a mask through the maximum between-class variance(OTSU)method and construct the measurement matrix with speckle patterns.Then,the correlated noise in GI can be effectively suppressed by employing the mask.From the simulation and experimental results,we can conclude that our method has the ability to improve the imaging quality compared with traditional GI method.
基金Supported by the National Key Research and Development Program of China(2018YFC1506500)。
文摘Fengyun-4 A(FY-4 A) belongs to the second generation of geostationary meteorological satellite series in China. Its observations with high frequency and resolution provide a better data basis for monitoring of extreme weather such as sudden flood disasters. In this study, the flood disasters occurred in Bangladesh, India, and some other areas of South Asia in August 2018 were investigated by using a rapid multi-temporal synthesis approach for the first time for removal of thick clouds in FY-4 A images. The maximum between-class variance algorithm(OTSU;developed by Otsu in 2007) and linear spectral unmixing methods are used to extract the water area of flood disasters. The accuracy verification shows that the water area of flood disasters extracted from FY-4 A is highly correlated with that from the high-resolution satellite datasets Gaofen-1(GF-1) and Sentinel-1 A, with the square correlation coefficient R2 reaching 0.9966. The average extraction accuracy of FY-4 A is over 90%. With the rapid multi-temporal synthesis approach used in flood disaster monitoring with FY-4 A satellite data, advantages of the wide coverage, fast acquisition,and strong timeliness with geostationary meteorological satellites are effectively combined. Through the synthesis of multi-temporal images of the flood water body, the influence of clouds is effectively eliminated, which is of great significance for the real-time flood monitoring. This also provides an important service guarantee for the disaster prevention and reduction as well as economic and social development in China and the Asia-Pacific region.
文摘This paper proposes an automatic method of pore combination recognition,which is an important feature to hardwood recognition.After extracting edge from wood microscopic cross-section, based on area histogram of the similar circle regions,the method classifies all regions into two classes with maximum between-class variance,so as to distinguish the pore from other textures,which are similar in shapes but different in sizes.Meanwhile, second objective function about average area of closed regions is used to improve the pore segmentation performance.At last,the method uses adjacency degree of pore set to judge pore combination.The experiments demonstrate that the task of pore segmentation can be completed successfully for all kinds of pore distribution and combination,and also the correct combinations of pores are given.
