Satellite image ship model recognition method under small sample condition

Abstract

The invention discloses a satellite image ship model recognition method under a small sample condition, and the method comprises the steps of obtaining a to-be-recognized ship remote sensing image of a target region, and carrying out the preprocessing of the to-be-recognized ship remote sensing image; inputting the preprocessed ship remote sensing image into a trained few-sample learning classifier and C SVM classifiers; and outputting a ship model corresponding to the ship remote sensing image subjected to multi-model fusion through an integration strategy, wherein the few-sample learning classifier and the C SVM classifiers measure distance information between the to-be-identified image and different types of targets in the small sample support set by using metric learning on the basis of a metric learning technology, so that the data feature extraction and expression capability under a small sample condition is improved, and the target identification precision under the small sample condition is improved. And on the other hand, an ensemble learning method is adopted, a classic machine learning technology is combined, an ensemble strategy is designed, ship target model stable recognition under the small sample condition is achieved, and the ship target model recognition capability is achieved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a satellite image ship model recognition method under the condition of small samples. Background technique [0002] In recent years, with the continuous development of aerospace technology, the means of satellite image acquisition has become increasingly mature, and the resolution of images, including time resolution, spatial resolution, radiation resolution and spectral resolution, is constantly improving. At present, satellite imagery has broken through the bottleneck of data acquisition and is moving towards a new stage of comprehensive application, laying an important data foundation for the extraction of marine targets. Sea transportation is one of the most important modes of transportation at present, so the detection and identification of marine targets such as ship targets and port areas play a very important role in both military and civilian applica...

AI Technical Summary

Problems solved by technology

[0009] The main purpose of the present invention is to provide a satellite image ship model identification method under the condition of a small sample that at least partially solves the above technical problems, which can solve the above problems Ship target model recognition has problems such as few training sample data and low accuracy of type recognition

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