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This paper presented a high performance method for remote sensing image processing using CUDA-based GPU. And it introduced the process of several common algorithms in remote sensing image processing. Experiments were carried out and results showed that the computing speed of GPU was much faster than that of CPU.
In this paper, we propose a fuzzy neural network based on immune feedback learning (FNNBIFL) for the availability classifier of satellite images, which accelerates the learning speed, solves the problem of being trapped in the local minimum and improves the learning performance of fuzzy neural network. Using 122 satellite images, we compare the recognition results of the availability classifier trained...
This paper studies influencing factors on the structure of clouds and the availability of satellite remote sensing images on base of that, and puts forward that the cloud area, cloud thickness and cloud fragment are the main factors. Combined with immune coding algorithm, the cloud area can be calculated; with the impact patterns on images by atmospheric scattering, refraction, and so on, a method...
In this paper, a multi-texture-model for water extraction based on remote sensing imagery is proposed. The model is applied to extract inland water (including wide river, lake and reservoir) from high-resolution panchromatic images. Firstly directional variance is used to find river regions, and then grain table is adopted to avoid noise including objects that have similar directional variance characteristic...
In this paper, an integrated algorithm to detect bridge objects over rivers was introduced for satellite imagery interpretation. It is composed of two steps: first, segment the river from complex background using data driven strategy; second, detect the bridges in the shrink searching area using knowledge driven strategy. Considering the ubiety of the bridges and the surroundings, this paper focused...
In this paper, a complete procedure is proposed to analyze and classify the texture of an image based Bayesian network classifiers. We apply this procedure in the residential areas detection. A simple case of Bayesian network called naive Bayes classifier is used to learn the positive and negative samples and to infer about the unknown regions. In this paper, each texture feature vector is labeled...
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