A kind of hyperspectral image endmember extraction method and system

Abstract

The invention discloses a hyper-spectral image end member extraction method and a hyper-spectral image end member extraction system. Optimized variables in the problem of hyper-spectral image end member extraction correspond to nectar source locations in an artificial bee colony algorithm, and optimization of each nectar source is determined by a fitness function. Nectar collecting bees search for an optimal nectar source, and sends nectar source information to follower bees after search; the follower bees search for an optimal nectar source the second time, and use a selected optimal nectar source to update a previously obtained optimal solution; and when there is a nectar collecting bee not updating the nectar source in a preset period of time, the nectar collecting bee is transformed into an investigation bee, and the investigation bee compares the fitness value of a randomly selected nectar source with the fitting value of a nectar source used as an optimal solution and calibrates the nectar source used as an optimal solution. According to the invention, the end member extraction problem is converted into a combination optimization problem solving process based on the artificial bee colony algorithm, the advantages of the artificial bee colony algorithm are given full play, and the nectar source used as an optimal solution is calibrated by the investigation bee to reduce the risk that the optimization process is trapped into a local optimal solution.

Description

technical field [0001] The present invention relates to the technical field of hyperspectral images, more specifically, to a hyperspectral image endmember extraction method and system. Background technique [0002] A hyperspectral image is a spectral image with a spectral resolution on the order of 101. Due to the limited spatial resolution of imaging spectrometers, the problem of mixed pixels exists widely in hyperspectral images. The method to solve the mixed pixel problem is called mixed pixel decomposition, and its purpose is to analyze which substances (called end members) and their proportions (called abundance) are contained in the mixed pixel. [0003] At present, hyperspectral image endmember extraction methods are mainly hyperspectral image endmember extraction method based on ant colony algorithm (ACOEE), hyperspectral image endmember extraction method based on discrete particles (DPSOEE) and its derivative methods. These methods are based on The root mean squar...

AI Technical Summary

Problems solved by technology

[0005] In view of this, the present invention discloses a hyperspectral image endmember extraction method and system to solve the problem that the result of hyperspectral image endmember extraction easily falls into a local optimal solution

Images