Infrared and visible light image fusion method combining improved NSCT transformation and deep learning

An image fusion, deep learning technology, applied in neural learning methods, image enhancement, image data processing and other directions, can solve problems such as difficult image fusion

Pending Publication Date: 2021-04-16
西安中科立德红外科技有限公司
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Problems solved by technology

[0005] The purpose of the present invention is to solve the technical problem that existing infrared image and visible light image fusion methods are difficult to p

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  • Infrared and visible light image fusion method combining improved NSCT transformation and deep learning
  • Infrared and visible light image fusion method combining improved NSCT transformation and deep learning
  • Infrared and visible light image fusion method combining improved NSCT transformation and deep learning

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Embodiment Construction

[0054] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0055] An infrared and visible light image fusion method combining improved NSCT transformation and deep learning, aiming at grayscale image fusion, such as figure 1 shown, including the following steps:

[0056] 1) Image decomposition

[0057] Using the improved non-subsampling contourlet transform NSCT, the infrared image A and the visible light image B to be fused are respectively decomposed into multiple (at least two) scales and multiple (at least two) directions to obtain multiple infrared low-frequency subbands images, infrared high-frequency sub-band images, visible light low-frequency sub-band images, and visible light high-frequency sub-band images;

[0058] The improved non-subsampling contourlet transform NSCT is an NSCT transform using a fusion filter bank; the fusion filter bank is obtained by convolution of filters of different scales a...

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Abstract

The invention relates to an infrared image and visible light image fusion method, in particular to an infrared and visible light image fusion method combining improved NSCT transformation and deep learning. The invention aims to solve the technical problem that an existing infrared image and visible light image fusion method is difficult to carry out rapid and effective image fusion, and provides an infrared and visible light image fusion method combining improved NSCT transformation and deep learning. According to the method, infrared and visible light image fusion is carried out in combination with improved NSCT transformation and deep learning to generate a fusion result image conforming to a human eye vision system. An improved non-subsampled contourlet transform NSCT is adopted to perform adaptive decomposition on a to-be-fused image, and deep learning is utilized to determine a fusion weight for a sub-band image of a corresponding scale. By adopting the method of the invention, the infrared image and the visible light image are fused, image details and spectral information can be enriched, the resolution is improved, and people can generate more complete scene perception.

Description

technical field [0001] The invention relates to a fusion method of an infrared image and a visible light image, in particular to an infrared and visible light image fusion method combining improved NSCT transformation and deep learning. Background technique [0002] Image sensors with different spectra sometimes have better complementary characteristics. For example, the infrared image sensor is based on the difference in the infrared radiation of the object, which reflects the thermal radiation characteristics of the object. Since the acquisition of the infrared image does not depend on the external light, it can overcome the influence of the weather environment, etc., and obtain excellent images at night or in fog. Target information in weather and other conditions, so it has the characteristics of working around the clock. The visible light image sensor is based on the different reflection capabilities of objects to visible light, reflecting the visible light reflection ...

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Application Information

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IPC IPC(8): G06T5/50G06K9/62G06N3/08
Inventor 王曰尧刘伟郭德福王鹏闫福文陈继铭
Owner 西安中科立德红外科技有限公司
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