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Visible light and infrared image fusion algorithm based on UDCT (Uniform Discrete Curvelet Transform) and PCNN (Pulse Coupled Neural Network)

An infrared image and fusion algorithm technology, applied in the field of image processing, can solve the problems of inconspicuous details, inability to judge the image to be fused, unclear fusion image, etc.

Active Publication Date: 2017-01-11
SICHUAN UNIV
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

[0005] In view of the above-mentioned prior art, the purpose of the present invention is to provide a visible light and infrared image fusion algorithm based on UDCT and PCNN, to solve the problems of the prior art due to the inability to judge the similarity of the low-frequency information of the image to be fused and the inability to judge the richness of the details of the source image. The resulting fusion image is not clear, the details are not obvious and other technical problems

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  • Visible light and infrared image fusion algorithm based on UDCT (Uniform Discrete Curvelet Transform) and PCNN (Pulse Coupled Neural Network)
  • Visible light and infrared image fusion algorithm based on UDCT (Uniform Discrete Curvelet Transform) and PCNN (Pulse Coupled Neural Network)
  • Visible light and infrared image fusion algorithm based on UDCT (Uniform Discrete Curvelet Transform) and PCNN (Pulse Coupled Neural Network)

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Embodiment 1

[0045] In view of the excellent performance of UDCT transformation, this paper applies it to the fusion method of infrared and visible light images. This algorithm can be summarized as the following three steps:

[0046](1) After decomposing the source images of the visible light image and the infrared image through UDCT transformation, the UDCT subband coefficients of different scales and directions can be obtained. It contains low frequency and high frequency UDCT coefficients.

[0047] (2) Use different methods to fuse each scale layer according to specific rules, that is, use low-frequency coefficient fusion rules for low-frequency coefficients, and use high-frequency coefficient fusion rules to process high-frequency coefficients, and finally obtain the fused UDCT of each layer coefficient.

[0048] (3) The reconstructed image obtained by inverse transforming the fused UDCT coefficients of each layer is the fused image.

[0049] Fusion rules adopted by the algorithm

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Embodiment 2

[0090] In order to verify the effectiveness of the algorithm, the experiment uses two sets of registered infrared and visible light images of the same scene. Experimental images such as figure 2 shown. The method proposed by the present invention is compared with the method based on wavelet transform, the method based on non-subsampling wavelet transform, the method based on Contourlet transform, the method based on UDCT transform and the method based on generalized random walk. In the experiment, both wavelet transform and non-subsampling wavelet transform use 3-layer decomposition, and use Harr wavelet basis function, use the maximum coefficient rule to fuse high-frequency coefficients, and use the average rule to fuse low-frequency coefficients.

[0091] Applying different fusion methods to the figure 2 The experimental results of the Chinese ship image are as follows: image 3 shown. image 3 (a) and image 3 (b) Infrared image and visible light image of the ship, r...

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Abstract

The invention discloses a visible light and infrared image fusion algorithm based on UDCT (Uniform Discrete Curvelet Transform) and a PCNN (Pulse Coupled Neural Network), which relates to the technical field of image processing and solves the technical problems that the fused image is not clear and details are unobvious as the similarity of low-frequency information of a to-be-fused image can not be judged in the prior art, and the detail richness degree of a source image can not be judged. The algorithm of the invention mainly comprises steps: (1) after source images of the visible light image and the infrared image are subjected to UDCT decomposition, UDCT subband coefficients with different scales in different directions can be obtained, and the UDCT subband coefficients comprise low-frequency and high-frequency UDCT coefficients; and (2) according to a specific rule, a different mode is adopted for each scale layer for fusion processing, a low-frequency coefficient fusion rule is adopted for the low-frequency coefficients, a high-frequency coefficient fusion rule is adopted for the high-frequency coefficients, and finally, the UDCT coefficient for each layer after fusion can be acquired; and a reconstructed image obtained after inverse transforma on the UDCT coefficient for each layer after fusion is the fused image.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a visible light and infrared image fusion algorithm based on UDCT and PCNN. Background technique [0002] At present, using the fusion technology of visible light and infrared images to improve the quality of infrared images is a research hotspot in the field of infrared image enhancement, and multi-scale fusion technology is the mainstream research direction in this hotspot. The principle of multi-scale fusion technology is as follows: In the first step, the source image is decomposed into a series of sub-images through multi-scale transformation, and these sub-images have different scales, frequency and spatial characteristics. In the second step, fusion calculation is performed on the transformation coefficients of the source image according to specific fusion rules. In the third step, the fused transformation coefficients are inversely transformed by multi-scale dec...

Claims

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Application Information

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IPC IPC(8): G06T5/50
CPCG06T5/50G06T2207/10048G06T2207/20064G06T2207/20084G06T2207/20221
Inventor 何小海甘炜吴晓红
Owner SICHUAN UNIV
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