Total variation remote sensing image stripe removing method based on tensor decomposition

Abstract

The invention discloses a total variation remote sensing image stripe removing method based on tensor decomposition. A remote sensing image is decomposed into superposition of a target image, strip noise and random noise, and different regular term constraints are adopted for each component to form a target model; in order to ensure the similarity between recovery data and original data, a non-convex data fidelity term is introduced; meanwhile, a total variation regular term is introduced to constrain the piecewise smooth characteristic of the target image; and finally, low-rank Tucker decomposition and L21 norm joint constraint are adopted for strip noise, a detailed algorithm is given by adopting an alternating direction multiplier method to solve the model, a target image is recovered from an original image, and a simulation experiment result is given to verify the feasibility and effectiveness of the method.

Description

technical field [0001] The invention specifically relates to a total variation remote sensing image stripping method based on tensor decomposition, which can be used in military and civilian fields such as target detection, target recognition, and ground object analysis, and belongs to the technical field of image processing. Background technique [0002] With the development of remote sensing technology, hyperspectral remote sensing images usually include dozens or even hundreds of spectral band images. Because hyperspectral remote sensing images contain rich spatial and spectral information, hyperspectral remote sensing technology has attracted widespread attention in academia, and its applications include many aspects such as earth climate, agriculture and military affairs. However, hyperspectral remote sensing imaging sensors will inevitably produce band noise in the process of collecting data. The main cause of this is the inconsistent response calibration error betwee...

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Problems solved by technology

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art, and provide a total variational remote sensing image stripping method based on tensor decomposition, which solves the problem that single-frame image stripping in the prior art will destroy the intrinsic properties of hyperspectral data. The problem of spectral continuity of

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