Multi-source image fusion method

A fusion method and source image technology, applied in the field of image fusion, can solve the problems of consuming a lot of time, ignoring the overall picture of the image, occupying a lot of memory, etc., to improve the visual effect and reduce the effect of "scratch".

Inactive Publication Date: 2011-02-09
CHONGQING UNIV
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Problems solved by technology

Pixel-level image fusion is mainly for the initial image data, and its purpose is mainly image enhancement, image segmentation and image classification, so as to provide better input information for manual interpretation of images or further feature-level fusion, pixel-level image fusion, relying on Due to the sensitivity of sensor sensing devices, high-resolution sensors are required for long-distance images; feature-level image fusion refers to the process of extracting feature information from each sensor image, and performing comprehensive analysis and processing. The extracted feature information is The sufficient

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[0036] The preferred embodiments of the present invention will be described in detail below.

[0037] Overall steps:

[0038] Such as figure 1 As shown, a multi-source image fusion method, the steps are:

[0039] In the image feature extraction stage:

[0040] 1) Use the wavelet kernel function to establish a multi-scale support filter for the image A to be fused and the image B to be fused;

[0041] 2) Use a multi-scale support filter to perform support transformation (ie SVT transformation) on the image to be fused to form high and low frequency information;

[0042] 3) Use anti-aliasing contourlet transform method (ie: NACT transform) to process high and low frequency information to obtain high and low frequency anti-aliasing information;

[0043] In the image fusion stage:

[0044] 4) For the low-frequency anti-aliasing information of each image to be fused, pulse coupled neural network (PCNN) fusion rules are used to select the low-frequency anti-aliasing information that can be trig...

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Abstract

The invention discloses a multi-source image fusion method. The method comprises the following steps of: in an early feature extraction stage, combining wavelet kernel-based support transform with anti-aliasing contourlet, wherein on one hand, direction information which cannot be extracted by the support transform is increased, and on the other hand, an aliasing phenomenon generated in contourlet transform is eliminated; and in an image fusion stage, performing fusion judgment on low frequency signals of each fused image by establishing a high frequency judgment device by adopting a pulse coupled neural network, and performing the fusion judgment on high frequency signals of each fused image by adopting an absolute value maximum selection rule. Therefore, effective fusion of high and low frequency signals is realized.

Description

technical field [0001] The invention relates to the field of image fusion, in particular to a multi-source image fusion method. Background technique [0002] The processing of image fusion in the prior art is usually at the pixel level, feature level, and decision-making level. Pixel-level image fusion is mainly for the initial image data, and its purpose is mainly image enhancement, image segmentation and image classification, so as to provide better input information for manual interpretation of images or further feature-level fusion, pixel-level image fusion, relying on Due to the sensitivity of sensor sensing devices, high-resolution sensors are required for long-distance images; feature-level image fusion refers to the process of extracting feature information from each sensor image, and performing comprehensive analysis and processing. The extracted feature information is The sufficient representation or sufficient statistics of pixel information. Typical feature info...

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Application Information

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IPC IPC(8): G06T5/50
Inventor 尚赵伟庞庆堃唐远炎张太平张明新张凌峰
Owner CHONGQING UNIV
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