Method for fusing high-spectrum image and visible light image based on nonnegative matrix decomposition

A non-negative matrix factorization, hyperspectral image technology, applied in the field of remote sensing image processing

Active Publication Date: 2012-11-21
INST OF AUTOMATION CHINESE ACAD OF SCI +1
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Problems solved by technology

[0006] In order to overcome the inadequacy of the fusion of hyperspectral images and visible light images in the field where existing image fusion methods are not app...

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  • Method for fusing high-spectrum image and visible light image based on nonnegative matrix decomposition
  • Method for fusing high-spectrum image and visible light image based on nonnegative matrix decomposition
  • Method for fusing high-spectrum image and visible light image based on nonnegative matrix decomposition

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Embodiment Construction

[0031] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the following further describes the present invention in detail in conjunction with specific embodiments and with reference to the accompanying drawings. It should be pointed out that the described examples are only intended to facilitate the understanding of the present invention and do not have any limiting effect on it. The method used in the present invention can be installed and executed in the form of software on a personal computer, an industrial computer and a server, or the method can be made into an embedded chip and embodied in the form of hardware.

[0032] figure 1 A flowchart of a method for fusing a hyperspectral image and a visible light image based on non-negative matrix decomposition according to an embodiment of the present invention is given, and the method includes the following steps:

[0033] Step S1: unmixing the hyperspectral image by using the non...

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Abstract

The invention discloses a method for fusing a high-spectrum image and a visible light image based on nonnegative matrix decomposition. The method comprises the steps that the high-spectrum image is unmixed in a nonnegative matrix decomposition method based on sparsity constraint to obtain an end member spectrum curve; the mixed coefficient of each pixel in the image is solved by constrained quadratic programming according to the spectrum absorption curve of the visible light image and the end member spectrum curve obtained by unmixing; and the end member spectrum curve obtained by unmixing and the mixed coefficient of each pixel are linearly mixed to obtain the fused image of high spatial resolution and high high-spectrum images. The method disclosed by the invention solves the problem that spectra in some wave bands of the high-spectrum image are irrelevant to the visible light image. The high-spectrum image is unmixed by nonnegative matrix decomposition based on sparsity constraint to obtain a more accurate end member spectrum. At the same time the mixed coefficient of the pixel can be obtained by the constrained quadratic programming. The obtained fused image has high spatial resolution and high spectrum resolution.

Description

Technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a method for fusing a hyperspectral image and a visible light image based on non-negative matrix decomposition, which is used for the fusion of hyperspectral image and visible light image acquired by aerospace and aviation sensor platforms. Background technique [0002] In the field of remote sensing image processing, for optical sensors, image spatial resolution and spectral resolution are a pair of contradictory factors. To obtain images with high spatial resolution, you can only work with a single spectrum, and to obtain a high spectrum, you must reduce the spatial resolution. Hyperspectral images are used to detect the types of substances on the surface and the atmosphere, evaluate and measure the content of the substances reflected in the spectrum, determine the area ratio of each component in a spatial unit of spectral mixing, describe the spatial distrib...

Claims

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Application Information

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IPC IPC(8): G06T5/50
Inventor 王颖江碧涛潘春洪郭建恩张秀玲
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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