Visual keyword based remote sensing image semantic searching method

Abstract

The invention relates to a visual keyword based remote sensing image semanteme searching method. The method comprises the following steps: setting visual keywords which describe image contents in an image base; selecting a training image from the image base; extracting remarkable visual characteristics of each training image, wherein the remarkable visual characteristics include remarkable points, main dominant tone and texture; acquiring a key mode through a cluster center of a cluster algorithm; establishing a visual keyword hierarchical model by adopting a Gaussian mixture model; extracting the remarkable visual characteristics of all images in the image base, setting weight parameters, and constructing a visual keyword characteristic vector describing the image semanteme; and calculating the similarity between an image to be searched and all images according to the similarity criterion, and outputting a search result according to the high-low sequence of the similarity. The method can effectively improve the recall ratio and the precision ratio of image searching by establishing the correlation between low-layer remarkable visual characteristics and high-layer semantic information through the visual keywords, and the technical scheme provided by the invention has excellent expansibility.

Description

technical field

[0001] The invention relates to the technical field of image processing, and more specifically, to a remote sensing image semantic retrieval method based on visual keywords. Background technique

[0002] The application of remote sensing image data is facing the contradiction of "more data and less data". On the one hand, with the rapid development of aerospace and various sensor technologies, computer network technologies, and database technologies, various remote sensing image data products that can be obtained, especially high-spatial resolution remote sensing image data, are increasing at an alarming rate every day. On the other hand, in such a vast remote sensing image data warehouse, people generally feel that it is not easy to quickly find the target of interest. This is because remote sensing image data itself has the characteristics of space, diversity, complexity, and mass, which makes the current lack of effective retrieval methods for massive ...

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