Mean shift is a widely used clustering algorithm in image segmentation. However, the segmenting results are not so good as expected when dealing with the texture surface due to the influence of the textures. Therefore...Mean shift is a widely used clustering algorithm in image segmentation. However, the segmenting results are not so good as expected when dealing with the texture surface due to the influence of the textures. Therefore, an approach based on wavelet transform (WT), co-occurrence matrix (COM) and mean shift is proposed in this paper. First, WT and COM are employed to extract the optimal resolution approximation of the original image as feature image. Then, mean shift is successfully used to obtain better detection results. Finally, experiments are done to show this approach is effective.展开更多
China has experienced rapid rural transformation in the past four decades.Accompanying the rapid transformation is a significant rise in rural household income and a substantial fall in rural poverty.This paper examin...China has experienced rapid rural transformation in the past four decades.Accompanying the rapid transformation is a significant rise in rural household income and a substantial fall in rural poverty.This paper examines the evolutions of and the relationships between rural transformation(high-value agriculture and rural non-farm employment)and its outcomes(per capita rural income and rural poverty incidence)using provincial-level data.The results show that 31 provinces/autonomous regions/municipalities have undergone significant rural transformation,but the level and speed of rural transformation differed considerably.Moreover,an increased level of rural transformation is often associated with higher per capita rural income and reduced rural poverty incidence.Notably,a category of provincial rural transformation based on high-value agriculture and rural non-farm employment is also analyzed.We further discuss the likely impacts of institutions,policies,and investments(IPIs)on rural transformation and conclude with policy implications.展开更多
基金Project (No. 035115039) supported by the Scientific Committee of Shanghai, China
文摘Mean shift is a widely used clustering algorithm in image segmentation. However, the segmenting results are not so good as expected when dealing with the texture surface due to the influence of the textures. Therefore, an approach based on wavelet transform (WT), co-occurrence matrix (COM) and mean shift is proposed in this paper. First, WT and COM are employed to extract the optimal resolution approximation of the original image as feature image. Then, mean shift is successfully used to obtain better detection results. Finally, experiments are done to show this approach is effective.
基金The authors acknowledge the financial support from the Australian Centre for International Agricultural Research(ADP/2017/024)the National Natural Science Foundation of China(71934003)+1 种基金the National Social Science Fundof China(19ZDA002 and 22CJL003)the International Fund for Agricultural Development(2000000866).
文摘China has experienced rapid rural transformation in the past four decades.Accompanying the rapid transformation is a significant rise in rural household income and a substantial fall in rural poverty.This paper examines the evolutions of and the relationships between rural transformation(high-value agriculture and rural non-farm employment)and its outcomes(per capita rural income and rural poverty incidence)using provincial-level data.The results show that 31 provinces/autonomous regions/municipalities have undergone significant rural transformation,but the level and speed of rural transformation differed considerably.Moreover,an increased level of rural transformation is often associated with higher per capita rural income and reduced rural poverty incidence.Notably,a category of provincial rural transformation based on high-value agriculture and rural non-farm employment is also analyzed.We further discuss the likely impacts of institutions,policies,and investments(IPIs)on rural transformation and conclude with policy implications.
