A remote sensing image fusion method based on a dual-channel neural network

A remote sensing image fusion and neural network technology, applied in the field of remote sensing image fusion based on dual-channel neural network, can solve the problems of low fusion efficiency and low quality of remote sensing image fusion, and achieve improved preservation performance, accurate reconstruction, and comprehensive fusion Effect

Active Publication Date: 2019-06-14
NORTHWEST UNIV
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Problems solved by technology

[0005] In order to make full use of the advantages of deep learning, as well as the structural characteristics and correlations existing within and between images, to improve the accuracy of image fusion, the present invention proposes a The remote sensing image fusion method (DCCNN) based on dual-channel neural network adopts the idea of ​​ARSIS, extracts the spatial detail information from the panchromatic image through the deep learning model, and then uses the detail injection model to inject the detail information into each band of the upsampled multispectral image In order to obtain the required high-resolution multispectral image, solve the problems of low quality and low fusion efficiency of remote sensing image fusion in the prior art

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  • A remote sensing image fusion method based on a dual-channel neural network
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Embodiment

[0065] The present invention uses two kinds of satellite remote sensing images to verify the effectiveness of the proposed fusion algorithm; the spatial resolutions of panchromatic images and multispectral images that can be captured by IKONOS satellites are 1 meter and 4 meters respectively; panchromatic images provided by QuickBird satellites The spatial resolutions of the multispectral images and the multispectral images are 0.7 meters and 2.8 meters respectively; among them, the multispectral images acquired by the two satellites include four bands of red, green, blue and near-infrared; the size of the panchromatic images used in the experiment is 256× 256, the multispectral image size is 64×64.

[0066] In order to better evaluate the practicability of the fusion method, the present invention provides two types of experiments, respectively simulated image experiment and actual image experiment, wherein the simulated image experiment is to simultaneously reduce the spatial ...

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Abstract

The invention discloses a remote sensing image fusion method based on a dual-channel neural network, and the method comprises the steps of firstly, extracting the spatial detail information in a high-frequency component after the high-pass filtering of a panchromatic image through the joint learning of a dual-channel network by utilizing the ARSIS thought; then injecting spatial detail informationinto each waveband image of the multispectral image by using a detail injection model to obtain a required high-resolution multispectral image. According to the method, the advantages of deep learning are effectively utilized, the spatial detail information, different from multi-spectral image waveband images, of a panchromatic image is obtained through double-channel network joint training, andthe correlation between the interior of the image and the images is fully utilized, so that the detail reconstruction is more accurate. Meanwhile, the number of injected details is effectively controlled by using the detail injection model, so that the spatial information storage performance of the fusion algorithm is remarkably improved, and the spectral characteristics of the original multispectral image are well kept.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a remote sensing image fusion method based on a dual-channel neural network. Background technique [0002] With the development of remote sensing technology, remote sensing image data obtained by various satellite sensors provides abundant resources for human observation of the earth, and has made important contributions to a deeper understanding of the world. For remote sensing images, their spatial and spectral resolutions contradict each other. Panchromatic images have high spatial resolution, but less spectral information, and cannot display the color of ground features; multispectral images have rich spectral information, but lower spatial resolution. By fusing panchromatic images with multispectral images, multispectral images with both high spatial and high spectral resolutions will be obtained to meet human needs. [0003] At present, remote sensing...

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Application Information

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IPC IPC(8): G06T3/40
Inventor 彭进业刘璐王珺阎昆吴振国章勇勤张二磊罗迒哉祝轩李展艾娜
Owner NORTHWEST UNIV
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