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Data visualization has been applied more and more recently because there is large scale of data to be processed. It can be used to show the data in a more effective and comprehensive way. Micro-Credit Companies (MCCs) have mushroomed in China in recent years. There are over 8000 MCCs in China by the end of March, 2014, reported by the People's Bank of China. These companies are important compliment to Chinese finance system and they are of big help in the development of small and medium enterprises. In this paper, some visualization ways to show the development of MCCs in China are presented. The MCCs development data from 2011 to 2014 are analyzed. In order to compare the development of MCCs in different areas, clustering method based on K-Means is used and performed by SPSS. The sum of paid-in loans and outstanding loans of different clusters is shown in Excel by pie-chart year by year. The center point of each cluster is shown in radar chart. These charts can give direct information about the development of MCCs and show the different status of MCCs in different area.

Frame rate up-conversion is used to reduce large area flicker. In this paper, frame average interpolation and interpolation based on motion compensation are analyzed and the results are compared. Based on the differences that the interpolated pixel projects on the two connective frame, a simple and effective interpolation algorithm which is sum of the result of frame average and motion compensation is presented. Experiment results show that this mixed interpolation can maintain the advantages of motion compensation interpolation and at the same time use the motion vectors more safety, that makes it more appreciable in the still areas than motion compensation interpolation.