Target similarity matching algorithm of big data in remote sensing image based on Henon mapping Online publication date: Wed, 01-Dec-2021
by Qing Sun; Quanyuan Wu
International Journal of Information and Communication Technology (IJICT), Vol. 20, No. 1, 2022
Abstract: In order to overcome the problem of low matching accuracy in traditional big data target similarity matching algorithm of remote sensing image, this paper proposes a new target similarity matching algorithm based on Henon mapping. The randomness of big data target in remote sensing image is analysed by using the variation of Henon mapping invariant distribution. According to the randomness, the track of big data target in remote sensing image is selected to build a two-layer similarity matching model. The first layer of the model uses coarse granularity to reduce the dimension of big data, and the second layer uses the fine-grained representation of similar track set to output several tracks similar to the big data target of remote sensing image, so as to achieve the target similarity matching. The experimental results show that the proposed method has high matching accuracy, and the highest matching accuracy can reach 99.7%.
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