There is a transition region between objects and background in any gray image. Many valuable applications of image segmentation and edge detection based on transition region determination have been developed in recent...There is a transition region between objects and background in any gray image. Many valuable applications of image segmentation and edge detection based on transition region determination have been developed in recent years. But, the complexity of calculation for determining transition region is too high. It results in the very limitation of applications based on transition region. A new novel fast method for transition region determination is presented in this paper, which will reduce the complexity of calculation dramatically. Many experiments have showed that this algorithm is effective and correct and will lay a good foundation for applications based on transition region. Key words image segmentation - transition region - maximum point - efficient average gradient (EAG) CLC number TP 391.4 Biography: Zhang Ai-hua (1965-), male, Ph. D candidate, research direction: image processing.展开更多
The oceanic front is a narrow zone in which water properties change abruptly within a short distance.The sea surface temperature(SST) front is an important type of oceanic front,which plays a significant role in many ...The oceanic front is a narrow zone in which water properties change abruptly within a short distance.The sea surface temperature(SST) front is an important type of oceanic front,which plays a significant role in many fields including fisheries,the military,and industry.Satellite-derived SST images have been used widely for front detection,although these data are susceptible to influence by many objective factors such as clouds,which can cause missing data and a reduction in front detection accuracy.However,front detection in a single SST image cannot fully reflect its temporal variability and therefore,the long-term mean frequency of occurrence of SST fronts and their gradients are often used to analyze the variations of fronts over time.In this paper,an SST front composite algorithm is proposed that exploits the frontal average gradient and frequency more effectively.Through experiments based on MODIS Terra and Aqua data,we verified that fronts could be distinguished better by using the proposed algorithm.Additionally through its use,we analyzed the monthly variations of fronts in the Bohai,Yellow,and East China Seas,based on Terra data from 2000 to 2013.展开更多
文摘There is a transition region between objects and background in any gray image. Many valuable applications of image segmentation and edge detection based on transition region determination have been developed in recent years. But, the complexity of calculation for determining transition region is too high. It results in the very limitation of applications based on transition region. A new novel fast method for transition region determination is presented in this paper, which will reduce the complexity of calculation dramatically. Many experiments have showed that this algorithm is effective and correct and will lay a good foundation for applications based on transition region. Key words image segmentation - transition region - maximum point - efficient average gradient (EAG) CLC number TP 391.4 Biography: Zhang Ai-hua (1965-), male, Ph. D candidate, research direction: image processing.
基金Supported by the National Natural Science Foundation of China(No.41271409)
文摘The oceanic front is a narrow zone in which water properties change abruptly within a short distance.The sea surface temperature(SST) front is an important type of oceanic front,which plays a significant role in many fields including fisheries,the military,and industry.Satellite-derived SST images have been used widely for front detection,although these data are susceptible to influence by many objective factors such as clouds,which can cause missing data and a reduction in front detection accuracy.However,front detection in a single SST image cannot fully reflect its temporal variability and therefore,the long-term mean frequency of occurrence of SST fronts and their gradients are often used to analyze the variations of fronts over time.In this paper,an SST front composite algorithm is proposed that exploits the frontal average gradient and frequency more effectively.Through experiments based on MODIS Terra and Aqua data,we verified that fronts could be distinguished better by using the proposed algorithm.Additionally through its use,we analyzed the monthly variations of fronts in the Bohai,Yellow,and East China Seas,based on Terra data from 2000 to 2013.
