Hyperspectral image in-orbit compression method

Abstract

The invention discloses a hyperspectral image in-orbit compression method. The method comprises the following steps: step S1, according to similarities between hyperspectral image wavebands, performing self-adaptive spectrum grouping and waveband rearrangement on the wavebands to obtain an initial dictionary, compression dimensions, an optimal waveband sequence and a hyperspectral image with a rearranged optimall waveband sequence; step S2, compressing the hyperspectral image with the rearranged optimal waveband sequence to a characteristic space with low spectrum dimensions by use of the initial dictionary, a spectrum sparse characteristic and the structural characteristic of a spectrum curve to obtain a structural dictionary capable of maintaining the separability of the spectrum curve; step S3, extracting a substantial object area in the characteristic space, storing the substantial object area by use of a sparse matrix, and sampling a characteristic image in a background area in the characteristic space to obtain the deeply compressed background area; and step S4, decompressing the substantial object area stored by use of the sparse matrix, the deeply compressed background area and data of the structural dictionary, recovering each characteristic image, and obtaining the recovered hyperspectral image.

Description

technical field [0001] The invention relates to the technical fields of hyperspectral image processing, data compression, target detection, etc., in particular to an on-orbit hyperspectral image compression method. Background technique [0002] Compared with panchromatic images or multispectral images, hyperspectral images have very high spectral resolution. For example, the spectral resolution of hyperspectral remote sensing images acquired by the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) is about 10nm. Hyperspectral imagery provides a new means for target recognition, not only for identifying the shape of the target, but also for identifying the material of the target or finely classifying ground objects using hyperspectral resolution. In recent years, hyperspectral remote sensing images have been widely used in many fields such as geological exploration, archaeological discovery, abnormal target detection, and military operations. [0003] Compared with tra...

AI Technical Summary

Problems solved by technology

At present, there are few feature-level compression methods for hyperspectral images, which cannot meet the needs of practical applications.

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