The application of High Performance Computing (HPC) technology to remote sensing data processing is one solution to
meet the requirements of remote sensing real- or near-real-time processing capabilities. We presented a cluster-based
parallel processing system for HJ-1 satellites data, named Cluster Pro. This paper presents the basic architecture and
implementation of the system. We did imagery mosaic experiment with the Cluster Pro, where the HJ-1 CCD data in
Beijing city was used. The experiments showed that the Cluster Pro was a useful system to improve the efficiency of data
processing. Further work would focus on the comprehensive parallel design and implementations of remote sensing data
We present a new object-oriented land cover classification method integrating raster analysis and vector analysis, which adopted improved Color Structure Code (CSC) for segmentation and Support Vector Machine (SVM) for classification using Very High Resolution (VHR) QuickBird data. It synthesized the advantage of digital image processing, Geographical Information System (GIS) (vector-based feature selection) and Data Mining (intelligent SVM classification) to interpret image from pixels to segments and then to thematic information. Compared with the pixelbased SVM classification in ENVI 4.3, both of the accuracy of land cover classification by the proposed method and the computational performance for classification were improved. Moreover, the land cover classification map can update
GIS database in a quick and convenient way.
This paper proposed a method for extracting Chinese characters in a gray scene image. This method makes use of the general features of. Chinese characters in scene image. First, the scene image is divided into partial regions. Some regions can be set as candidates of character regions with comparing spatial frequency and contrast. Then, the whole image is binarized using the dynamic thresholding method of gray-level image. Next the circumscribed squares of each candidate character regions are located according to the labeling results. Finally, the character regions are determined using the proximity of characters, co-linearity of characters and similarity of characters. The extraction rate is about 80.6% according to the experiments.
Conference Committee Involvement (1)
International Conference on Earth Observation Data Processing and Analysis