Hyperspectral endmember extraction method and device based on multi-objective differential evolution of sorting multiple variations
A differential evolution algorithm and endmember extraction technology, applied in the field of remote sensing image processing, can solve problems such as poor endmember extraction effect.
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Embodiment 1
[0065] This embodiment provides a hyperspectral endmember extraction method based on multi-objective differential evolution of sorting multi-variation, which converts the problem of hyperspectral end-member extraction into a multi-objective optimization problem, Differential evolution algorithm to balance the conflicts between multiple objectives, see figure 1 , the method specifically includes:
[0066] S1: Randomly initialize the population by integer coding, where the individual in the population is an end member candidate solution of the hyperspectral image;
[0067] S2: Using the multi-variation strategy operation to generate a mutation vector through the scaling factor parameter pool, where the mutation vector is used to increase the diversity of hyperspectral image endmembers;
[0068] S3: For the individual and variation vector in the population, use the binomial crossover operation to generate the test vector through the crossover control parameter pool, where the te...
Embodiment 2
[0114] Based on the same inventive concept, the second aspect of the present invention provides a hyperspectral endmember extraction device based on multi-objective differential evolution based on sorting multi-variation, which converts the problem of hyperspectral endmember extraction into a multi-objective optimization problem. The (μ+λ) multi-objective differential evolution algorithm to balance the conflict between multiple objectives, the device includes:
[0115] The population initialization module 201 is used to randomly initialize the population through integer coding, wherein the individual in the population is an end member candidate solution of the hyperspectral image;
[0116] The sorting multi-variation module 202 is used to use the multi-variation strategy operation to generate a mutation vector through the scaling factor parameter pool, wherein the mutation vector is used to increase the diversity of hyperspectral image endmembers;
[0117] The binomial crossov...
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