Remote sense image data intelligent search method based on content

Abstract

The present invention belongs to remote sensing image application field, especially a remote sensing image data intelligence searching method based on the content, intelligent search of the remote sensing image is processed according to the keyword searched by the remote sensing image, getting keyword includes following steps: step 1, classifying remote sensing image by unsupervised classification method to get classifying grid data; step 2, distributing classifying grid data by grid, providing opened man-machine interactive interface, and collecting tags added by all kinds image by the man-machine interactive interface; step 3, arranging collected tags, enhancing tags weight if having duplicate content, making high weight as content mark corresponding to the image part; step 4, providing content mark as searching keyword of remote sensing image. The invention provides a opening keyword acquirement pattern, having convenient implement, abound information, collecting information of remote sensing image data helping user, improving searching quality, having exactly searching effect.

Description

technical field [0001] The invention belongs to the application field of remote sensing images, in particular to a content-based intelligent search method for remote sensing image data. Background technique [0002] Intelligent search of remote sensing image data is a key technology in image information retrieval. With the rapid increase of remote sensing image data, how to retrieve the information that users really care about in the massive web-based image database is a technical difficulty that needs to be solved urgently. This involves artificial intelligence-based image information retrieval and extraction to assist users in information collection and data processing of a large amount of remote sensing image data from the Internet and local computers, improve image retrieval quality, and achieve precise search results. Metadata used for queries can generally be divided into two categories. One category is automatically formed during the data acquisition and production ...

AI Technical Summary

Problems solved by technology

[0005] Since the traditional content-based remote sensing image object retrieval technology mainly uses retrieval methods based on color, texture and shape matching and defining metadata information, the implementation needs to complete the matching steps based on color, texture and shape with the help of experts, and consider complex Metadata definition and other links, not only the implementation process is complicated, but also the effect is not ideal: there is uncertainty in the method based on color, texture and shape matching, and it is difficult to obtain correct results; the retrieval method based on metadata information must define metadata in advance information, and once the metadata is defined, it often cannot be changed during retrieval, which may cause the problem that the content to be retrieved is not defined in the metadata and cannot be retrieved

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