This paper presents the method which improved the efficiency of information extraction based on feature unit of high-resolution remotely sensed image. To improve the precision of image processing

this paper applied image rough-classification based on large scale and precise-segmentation based on different scales. This paper used parallel computing method to improve the speed of image processing. For the data partition method of parallel computing of remotely sensed image

this paper summarized the general data partition methods and gave the general impelmentaiton method of data symmetrical partition method. After the characteristic analysis of the some special of remotely sensed image

this paper gave the mechanism of improving the efficiency of data partition and presented a new scale data asymmetric partition method

and gave the analysis and implementation of the new method. For the image parallel processing based on remotely sensed image database

this paper presented a new data distributing method. The analysis results show that the new methods can improve the efficiency of parallel computing for some special remotely sensed image in the special condition.