Gradient filtering and PCA-based unmanned aerial vehicle (UAV) image and multispectral image fusion method

Abstract

The invention discloses a gradient filtering and PCA-based unmanned aerial vehicle image and multispectral image fusion method which comprises the following steps: images of the same pixel size are obtained via image registration operation and resampling operation, then two sets of independent multiband images that are same in spatial range are obtained via cutting operation, the two sets of independent multiband images are respectively a multispectral remote sensing image which is large in wave band quantity and low in spatial resolution and a three-wave-band unmanned aerial vehicle image which is high in spatial resolution, the two sets of independent multiband images are subjected to principal component transformation operation, specific filtering operators of all principal components of the unmanned aerial vehicle image are chosen to be subjected to gradient filtering operation, and therefore texture information of three principal components of the unmanned aerial vehicle image can be obtained; the texture information, as a certain weight, is superposed onto first three principal components of the multispectral remote sensing image which is large in wave band quantity and low in spatial resolution, then the principal components can be reinforced, the reinforced principal components are subjected to principal component inverse transformation operation, and therefore a multispectral fusion result which is high in wave band quantity and high in spatial resolution can be obtained. Via use of the method, limitation of a tradition fusion method in single wave band panchromatic data and multispectral image fusion, diverse data can take part in the image fusion, and the fusion result is enabled to have rich spatial detail information.

Description

technical field [0001] The present invention relates to the field of remote sensing image processing data fusion, more specifically, to a multi-band image and multi-band image fusion technology, which is an extended fusion technology using gradient filtering technology and Principal Component Analysis (PCA). . technical background [0002] Remote sensing data is the basis of remote sensing research. However, due to the limitations of remote sensing platforms and sensors, the spatial resolution of remote sensing images is difficult to be compatible with multispectral information. Therefore, the general sensor is designed to simultaneously acquire single-band panchromatic data with high spatial resolution. And multi-spectral data with low spatial resolution but multi-band; this production mode has greatly stimulated the rapid development of a technology in the field of remote sensing research-image fusion technology. Image fusion technology has been developed for a long time....

AI Technical Summary

Problems solved by technology

UAVs can provide red, green and blue three-band remote sensing images with extremely high spatial resolution. The spatial resolution is high, but the spectral resolution is not fine enough. It can be considered for fusion with data such as WorldView-2 (or 3)

This requires fusion technology to meet the fusion of multi-band images and multi-band images, which is also a requirement that most current fusion algorithms cannot meet.

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