Hyperspectral image reconstruction method adopting deep learning

Abstract

The invention discloses a hyperspectral image reconstruction method adopting deep learning. The hyperspectral image reconstruction method comprises steps that 1) a hyperspectral training data set is trained by adopting a sparse coding way to acquire a neural network; 2) space spectrum modulation of an original hyperspectral image of a target scene is carried out to acquire a two-dimensional sensor image; 3) the two-dimension sensor image acquired in the step 2) is reconstructed by using the neural network, and the reconstructed hyperspectral image of the target scene is acquired. The hyperspectral image reconstruction method is advantageous in that a problem of low hyperspectral imaging speed is solved, and the hyperspectral image having higher resolution is acquired.

Description

technical field [0001] The invention relates to the field of hyperspectral image reconstruction, in particular to a method for reconstructing hyperspectral images using deep learning. Background technique [0002] In today's era, ordinary cameras can no longer meet people's requirements in some fields. In actual work and production, it is often necessary to obtain actual information through higher-resolution images. For example, doctors often need to obtain the image information of a certain part of the patient's body to conduct a more in-depth pathological analysis. At this time, ordinary cameras cannot meet this requirement. However, in related technologies, a color camera obtains color records of a scene by adding red, green, and blue filters to the sensor, which often ignores the spectral details of the scene. Therefore, in order to collect three-dimensional hyperspectral images, time-sharing scanning is often adopted (that is, by sacrificing time resolution or spatial...

AI Technical Summary

Problems solved by technology

For example, doctors often need to obtain image information of a certain part of the patient's body to conduct a more in-depth pathological analysis. At this time, ordinary cameras cannot meet this requirement.

In related technologies, color cameras obtain the color records of the scene by adding red, green, and blue filters to the sensor respectively, which often ignores the spectral details of the scene.

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