Three-step hyperspectral image fusion method based on spectrum reconstruction

Abstract

The invention relates to a three-step hyperspectral image fusion method based on spectrum reconstruction, i.e., principal component analysis image fusion is perfected through processing methods of wave band selection and spectrum reconstruction, so that a better fusion effect is obtained. The method is as follows: 1) hyperspectral image data and high spatial resolution image data to be fused are obtained through a human-computer interaction interface module, and related parameters are initialized; 2) through a hyperspectral image wave band selection module, a wave band is designed and a matrix is selected, and wave band selection is performed on an initial hyperspectral image; 3) through a hyperspectral image-high spatial resolution image data fusion module, principle component analysis fusion is performed on an input image; 4) through an spectrum reconstruction module, high-precision spectrum reconstruction is performed on an initial fusion image; and 5) through a fusion result output module, a final fusion result is output. The three-step hyperspectral image fusion method based on spectrum reconstruction has the advantages that the data volume to be fused is reduced, the spectrum distortion is reduced, the spectrum retentivity is improved, the image quality is enhanced, and the fusion quality is good, and the method has a wide range of application.

Description

technical field [0001] The invention relates to a three-step hyperspectral image fusion method based on spectral reconstruction, which is suitable for a hyperspectral image processing system and belongs to the field of hyperspectral remote sensing image processing. Background technique [0002] With the emergence of the concept of imaging spectrum in the early 1980s, optical remote sensing has entered a new stage—the hyperspectral remote sensing (Hyperspectral Remote Sensing) stage. Hyperspectral remote sensing refers to the remote sensing science and technology that integrates detector technology, precision optical machinery, weak signal detection, computer technology, and information processing technology, and can obtain images with high spectral resolution. It is the current pattern recognition and remote sensing information processing technology. A research hotspot in the research field. [0003] Compared with conventional remote sensing images, hyperspectral remote sen...

AI Technical Summary

Problems solved by technology

Although the first three methods improve the spatial resolution of images in each band of hyperspectral data, the image spectrum after fusion is seriously distorted, easily adding noise, and even affecting the visual effect; while the wavelet transform method maintains the original spectral characteristics, but the spatial resolution less effective

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