Electrophoretic display(EPD) technology has become one of the main supporting pillars of the electronic paper display industry.Despite its benefits,the EPD technology suffers from several disadvantages such as non-fix...Electrophoretic display(EPD) technology has become one of the main supporting pillars of the electronic paper display industry.Despite its benefits,the EPD technology suffers from several disadvantages such as non-fixed threshold voltage value for gray scale display.In addition,the display has to repeatedly refresh between white and black states to eliminate ghost image when it needs to update a new image.The traditional driving waveform for the EPD includes four stages: erasing the original image,resetting to black state,clearing to white state,and writing a new image.A flicker can be found when transferring between two adjacent stages.A new driving waveform based on the improvement of activation pattern is proposed to weaken the ghost image and reduce the flicker.Experimental results show that the proposed driving waveform could weaken the ghost image effectively and reduce the number of flickers by 50%.Compared with the traditional driving waveform,the driving waveform of this work has a better performance.展开更多
Most existing classification studies use spectral information and those were adequate for cities or plains. This paper explores classification method suitable for the ALOS （Advanced Land Observing Satellite） in moun...Most existing classification studies use spectral information and those were adequate for cities or plains. This paper explores classification method suitable for the ALOS （Advanced Land Observing Satellite） in mountainous terrain. Mountainous terrain mapping using ALOS image faces numerous challenges. These include spectral confusion with other land cover features, topographic effects on spectral signatures （such as shadow）. At first, topographic radiometric correction was carried out to remove the illumination effects of topography. In addition to spectral features, texture features were used to assist classification in this paper. And texture features extracted based on GLCM （Gray Level Co- occurrence Matrix） were not only used for segmentation, but also used for building rules. The performance of the method was evaluated and compared with Maximum Likelihood Classification （MLC）. Results showed that the object-oriented method integrating spectral and texture features has achieved overall accuracy of 85.73% with a kappa coefficient of 0.824, which is 13.48% and o.145 respectively higher than that got by MLC method. It indicated that texture features can significantly improve overall accuracy, kappa coefficient, and the classification precision of existing spectrum confusion features. Object-oriented method Integrating spectral and texture features is suitable for land use extraction of ALOS image in mountainous terrain.展开更多
基金Project(2011D039)supported by Guangdong Innovative Research Team Program,China
文摘Electrophoretic display(EPD) technology has become one of the main supporting pillars of the electronic paper display industry.Despite its benefits,the EPD technology suffers from several disadvantages such as non-fixed threshold voltage value for gray scale display.In addition,the display has to repeatedly refresh between white and black states to eliminate ghost image when it needs to update a new image.The traditional driving waveform for the EPD includes four stages: erasing the original image,resetting to black state,clearing to white state,and writing a new image.A flicker can be found when transferring between two adjacent stages.A new driving waveform based on the improvement of activation pattern is proposed to weaken the ghost image and reduce the flicker.Experimental results show that the proposed driving waveform could weaken the ghost image effectively and reduce the number of flickers by 50%.Compared with the traditional driving waveform,the driving waveform of this work has a better performance.
基金supported jointly by Key Laboratory of Geo-special Information Technology, Ministry of Land and Resources (Grant No. KLGSIT2013-12)Knowledge Innovation Program (Grant No. KSCX1-YW-09-01) of Chinese Academy of Sciences
文摘Most existing classification studies use spectral information and those were adequate for cities or plains. This paper explores classification method suitable for the ALOS （Advanced Land Observing Satellite） in mountainous terrain. Mountainous terrain mapping using ALOS image faces numerous challenges. These include spectral confusion with other land cover features, topographic effects on spectral signatures （such as shadow）. At first, topographic radiometric correction was carried out to remove the illumination effects of topography. In addition to spectral features, texture features were used to assist classification in this paper. And texture features extracted based on GLCM （Gray Level Co- occurrence Matrix） were not only used for segmentation, but also used for building rules. The performance of the method was evaluated and compared with Maximum Likelihood Classification （MLC）. Results showed that the object-oriented method integrating spectral and texture features has achieved overall accuracy of 85.73% with a kappa coefficient of 0.824, which is 13.48% and o.145 respectively higher than that got by MLC method. It indicated that texture features can significantly improve overall accuracy, kappa coefficient, and the classification precision of existing spectrum confusion features. Object-oriented method Integrating spectral and texture features is suitable for land use extraction of ALOS image in mountainous terrain.
