Hyperspectral remote sensing image characteristic extraction method and device

Abstract

The embodiment of the invention discloses a hyperspectral remote sensing image characteristic extraction method and device. Rapid characteristic extraction is achieved for a hyperspectral remote sensing image through collaborative operation conducted by a CPU and a GPU. The algorithm logic control function, the data reading function and the data storage function are achieved on the CPU. The function of large-scale operation such as noise estimation and covariance matrix calculation is achieved on the GPU. When noise estimation is conducted, the hyperspectral remote sensing image is divided into a plurality of image blocks and noise estimation is executed through multiple threads in parallel, and therefore the hyperspectral remote sensing image characteristic extraction speed is increased.

Description

technical field [0001] The invention relates to the technical field of image processing, and more specifically, to a method and device for extracting features of a hyperspectral remote sensing image. Background technique [0002] The large number of bands in hyperspectral remote sensing images provides extremely rich spectral, radiometric, and geometric information for the extraction of ground feature information, which is helpful for more detailed ground feature classification and target recognition. However, the increase in spectral bands will also lead to information loss. Redundancy and data processing complexity increase, so feature extraction plays a very important role in hyperspectral remote sensing image processing. [0003] In the process of implementing the present invention, the inventors found that the prior art uses CPU to extract features of hyperspectral remote sensing images, and the feature extraction rate is relatively low. Contents of the invention [...

AI Technical Summary

Problems solved by technology

[0002] The large number of bands in hyperspectral remote sensing images provides extremely rich spectral, radiometric, and geometric information for the extraction of ground feature information, which is helpful for more detailed ground feature classification and target recognition. However, the increase in spectral bands will also lead to information loss. Redundancy and increased data processing complexity, therefore, feature extraction plays a very important role in hyperspectral remote sensing image processing

[0003] In the process of realizing the present invention, the inventor found that the prior art extracts hyperspectral remote sensing image features through CPU, and its feature extraction rate is low

Images