Remote sensing image retrieval method and remote sensing image retrieval device based on rotation/zooming/translation invariance

Abstract

The invention relates to the field of remote sensing image retrieval technology, and particularly to a remote sensing image retrieval method and a remote sensing image retrieval device based on rotation / zooming / translation invariance. The retrieval method comprises the steps of a, after performing image transformation processing on each image in an image database, extracting edge point pixels of each image, and constructing a transaction set of each image; b, extracting an association rule in the image through the transaction set of each image; and c, calculating an association rule similarity between the to-be-retrieved image and the retrieval images in the image database according to a support degree and confidence index, and performing image retrieval according to the association rule similarity between the to-be-retrieved image and the retrieval images in the image database. According to the remote sensing image retrieval method and the remote sensing image retrieval device, the association rule of the remote sensing image is extracted from the constructed transition set; and then the association rule similarity between the to-be-retrieved image and the retrieval images in the image database is determined, thereby realizing remote sensing image retrieval and improving remote image retrieval accuracy.

Description

technical field [0001] The invention relates to the technical field of remote sensing image retrieval, in particular to a remote sensing image retrieval method and device invariant to rotation, scaling and translation. Background technique [0002] Remote sensing images have the characteristics of large image format and many and complex image contents. The phenomenon of "same object with different spectrum" and "different object with same spectrum" is very common, which brings great difficulty to the retrieval of remote sensing images. Image retrieval is to search for images containing specified features or similar content in the database. The current mainstream content-based image retrieval (Content-Based Image Retrieval, CBIR) method can integrate image processing, information retrieval, machine learning, computer vision, artificial intelligence, etc. The knowledge in many fields uses the visual features automatically extracted from the image as the description of the imag...

AI Technical Summary

Problems solved by technology

The "semantic gap" between low-level features and high-level semantic information hinders the development and application of remote sensing image retrieval

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