Hyperspectral image ground object classification method based on spectral segmentation and homogeneous region detection

Abstract

The invention discloses a hyperspectral image ground object classification method based on spectral segmentation and homogeneous region detection. The method comprises the following steps: constructing a homogeneous region detection module, a feature extraction sub-network cluster and a feature fusion module; constructing a hyperspectral classification model; generating a training set; training ahyperspectral classification model; and performing ground object classification on the to-be-classified pixels. According to the invention, the homogeneous region detection module is constructed and used for correcting the input hyperspectral image block, the corrected image block is segmented along the spectral dimension by using the spectral segmentation strategy, the plurality of parallel feature extraction sub-networks are constructed and trained, feature fusion is carried out, and the classification result is obtained, so that the invention has the advantage of high hyperspectral image classification precision, and the method can be used for ground object target recognition in the fields of agricultural ecological monitoring, geological detection and the like.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a hyperspectral image classification method based on spectral segmentation and homogeneous region detection in the technical field of image classification. The invention can be used for land use analysis, environment detection, resource exploration and urban planning for object recognition. Background technique [0002] Hyperspectral remote sensing is the abbreviation of hyperspectral resolution remote sensing. It is a technology to obtain many very narrow and spectrally continuous image data in the visible, near-infrared, mid-infrared and thermal infrared bands of the electromagnetic spectrum. Hyperspectral imaging remote sensing has been widely used in geological exploration, geological mapping, vegetation ecological monitoring, precision agriculture, atmospheric environment, environmental monitoring, marine remote sensing, food safety, product quality monitoring...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to address the shortcomings of the above-mentioned prior art, and propose a hyperspectral image classification method based on spectral segmentation and homogeneous region detection, which is used to solve the lack of consideration of hyperspectral image heterogeneous pixels in the prior art , the classification accuracy is not high, the model has a large amount of calculation, and the classification speed is slow

Images