Decomposition method for mixed pixels of hyperspectral image

Abstract

The present invention discloses a decomposition method for mixed pixels of a hyperspectral image. According to the method, in a process of using an NMF algorithm to decompose the mixed pixels, an SC-SVM algorithm is adopted to solve the quantity of end members and spectral vectors in the mixed pixels, the quantity of the end members can be actively recognized and the spectral vectors of the end members can be marked by the SC-SVM algorithm, thereby solving a basis matrix from the NMF algorithm; and a coefficient matrix (abundance matrix) is calculated by a non-negative matrix decomposition algorithm, gradual iteration to convergence is carried out by minimizing an objective function to calculate a wanted result, and finally achieve a purpose of decomposition of the mixed pixels.

Description

technical field [0001] The invention relates to a method for decomposing mixed pixels of a hyperspectral remote sensing image, in particular to a method for decomposing a mixed pixel of a hyperspectral image based on an SC-SVM NMF algorithm, and belongs to the technical field of hyperspectral remote sensing image processing. Background technique [0002] Remote Sensing (RS) refers to the comprehensive observation technology of the earth's surface from long-distance space (spaceflight) or outer space (aviation) that began in the 1960s. Remote sensing refers to indirect observation and monitoring from long-distance or outer space, without touching the target, to obtain relevant information about the target, phenomenon and area from the optical point of view, so as to carry out data fusion analysis and inference, and finally achieve the goal of obtaining the required target information. means, technology and science. Hyper-spectral image remote sensing technology (Hyper-spectr...

AI Technical Summary

Problems solved by technology

Remote sensing technology, its development process is after panchromatic (that is, black and white) photography and color image stage, multispectral remote sensing developed rapidly in the second half of the 20th century, made great progress, and has been applied to the environment and In the field of resource detection, its resolution is still within the wavelength range of the order of magnitude spectrum, and there are relatively few sampling points. With the development of science and technology, people's understanding of the earth's resources and the environment is getting deeper and deeper, and its application accuracy is becoming less and less accurate. To meet the demand, the requirement for the development of deeper resolution is more urgent, mainly reflected in the deepening and improvement of spatial resolution and spectral resolution

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