Hyperspectral image denoising method and system based on adaptive rank correction, and medium

Abstract

The invention discloses a hyperspectral image denoising method and system based on adaptive rank correction and a medium. According to the hyperspectral image denoising method, a hyperspectral image denoising model based on adaptive rank correction is established for each matrix block degenerated hyperspectral image and a clean hyperspectral image initially estimated by matrix blocks. The adaptiverank correction penalty function is used to adaptively counteract the penalty of a nuclear norm to a large singular value, sparse noise is eliminated based on l2, 1 norm, an alternating direction multiplier algorithm is used to solve blocked clean images, and the blocked clean images are combined to acquire a final estimated clean hyperspectral image. According to the method, the problems that most existing hyperspectral denoising methods based on low-rank matrix recovery utilize nuclear norms to approach matrix ranks, so that singular values with large excessive penalty are caused, rank information is fixed, definition needs to be performed in advance, and the methods are inflexible can be solved. Gaussian noise, impulse noise, dead lines, stripes and other complex noise in the hyperspectral image can be removed.

Description

technical field [0001] The invention relates to hyperspectral image denoising technology, in particular to a hyperspectral image denoising method, system and medium based on adaptive rank correction. Background technique [0002] Hyperspectral imagery (HSI) contains rich spectral information and is widely used in environmental monitoring, urban planning, geological exploration, and agricultural and forestry production. During the imaging and transmission process, due to the influence of many complex factors, the acquired hyperspectral image contains various types of mixed noise, such as Gaussian noise, impulse noise, banding, dead line, etc. These complex mixed noises not only affect image quality, but also cause great trouble to subsequent applications. Therefore, proposing an effective hyperspectral image denoising method is of great significance for hyperspectral image processing analysis and subsequent applications. [0003] Traditional 2D image denoising methods, such...

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Problems solved by technology

[0006] The technical problem to be solved by the present invention: In order to solve most of the existing hyperspectral denoising methods based on low-rank matrix restoration, the nuclear norm is used to approximate the matrix rank, which leads to excessive punishment. The large singular value and rank r information are fixed and need to be defined in advance so that the method Inflexible and other problems, provide a hyperspectral image denoising method, system and medium based on Adaptive Rank Correction (ARC), the invention can remove Gaussian noise, impulse noise, dead lines and bands and other complex noise

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