Multi-index fused hyperspectral remote sensing image dimensionality reduction method

Abstract

The invention discloses a multi-index fused hyperspectral remote sensing image dimensionality reduction method. Dimensionality reduction can be efficiently and rapidly achieved through a band selection method. At first, subspace decomposition is carried out on obtained hyperspectral remote sensing images, the entropy and the standard distance between mean values of a band and correlation coefficients between bands are fused by means of a method based on Choquet fuzzy integral in each subspace, and then band selection is carried out according to unified indexes to achieve data dimension reduction.

Description

technical field [0001] The invention relates to a multi-indicator fusion hyperspectral remote sensing image dimensionality reduction method, specifically using a Choquet fuzzy integral-based band selection method to complete dimensionality reduction of hyperspectral image data, and to process hyperspectral images quickly and efficiently. Spectral remote sensing image processing field. Background technique [0002] Remote Sensing (Remote Sensing) is a technology that uses the principle of electromagnetic waves to obtain distant signals and image them, and can feel and perceive distant things remotely. It is a new science. With the improvement of computer technology and optical technology, remote sensing technology has also been developed rapidly. In recent years, a variety of remote sensing satellites have been successfully launched, which has promoted the remote sensing data acquisition technology towards three high (high spatial resolution, high spectral resolution and hig...

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Problems solved by technology

Although the feature extraction method is convenient and fast, it is realized through a certain transformation, so it will destroy the physical characteristics of the original band

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