Classified identification algorithm of ship targets based on manifold distance characteristic

Abstract

The invention discloses a classified identification algorithm of ship targets based on the manifold distance characteristic. According to the algorithm, the similarity measuring standard among target objects is provided on the basis of the distance weight among samples represented by weighted corrected local anti-entropy operators. Compared a traditional distance measuring standard, the similarity measuring standard can reflect the practical space distribution of the objects more effectively; and neighbor samples are preprocessed and screened based on the standard, the classification efficiency of a probability generation model is improved, and the real-time processing requirement for ship target classified identification is met.

Description

technical field [0001] The invention relates to the field of computer application technology, in particular to a ship target classification and recognition algorithm based on manifold distance representation. Background technique [0002] As an important carrier at sea, the efficiency of automatic detection and identification of ships is related to the success or failure of our army's war to seize the sea to a certain extent. Especially in recent years, with the development of satellite remote sensing technology, the recognition algorithm based on optical remote sensing images has shown its own advantages, which has attracted great attention from scholars at home and abroad, and a series of theoretical reference and application value have emerged. Research results. [0003] Generally speaking, the key problem in solving target classification is how to cluster, and the most important factor in clustering is the measurement of similarity between target objects. Traditional si...

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However, in actual application, these existing algorithms lack a comprehensi

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