Image fusion method based on gradient domain guided filtering and improved PCNN

Abstract

The invention relates to an image fusion method based on gradient domain guided filtering and improved PCNN, and belongs to the field of image processing. The method comprises: firstly, detecting a source image according to three complementary image features of the structure, the definition and the contrast saliency of the image to obtain an initial decision diagram, the decision diagram model caneffectively and accurately measure the saliency of the features, and the performance of the method being greatly improved; then, in order to fully utilize the spatial consistency of the image and suppress the blocking effect in the image, optimizing the initial decision diagram by adopting gradient domain guided filtering to obtain an optimized decision diagram; secondly, performing weighting operation on the optimization decision diagram and the to-be-fused image to obtain an optimal decision diagram; and finally, in order to enable the fused image to more accord with the visual characteristics of human eyes, processing the optimized decision diagram by adopting the improved PCNN to obtain a final fused diagram. The method solves the problems that a traditional image fusion method is complex and low in efficiency and excessively depends on manual design, and meanwhile the image fusion quality is further improved.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to a multi-source image fusion method, which can be applied to various civil image processing systems. Background technique [0002] Image fusion refers to the process of merging the important information of two or more multi-source images by using a certain technology. The purpose is to make the obtained fused image fully utilize the information of different source images, so as to describe the scene information more accurately and comprehensively. As an important part of image fusion technology, the fusion of infrared and visible light images has higher definition, greater information content, more comprehensive information on targets and scenes, and is more suitable for human visual perception. It has been used in military, industrial and civilian applications. and other fields have been applied. In the civilian field, the application of infrared and visible light fus...

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Problems solved by technology

[0005] Aiming at the problems of halo artifacts and low contrast in the fused image obtained by the fusion method, we make full use of the edge smoothing and edge gradient preservation characteristics of the guided filter and the (pulse coupled neural network, PCNN) PCNN model's characteristics that are conducive to visual perception. A fusion method based on gradient domain guided filter and improved PCNN (GDGF-PCNN) is proposed, which can better preserve the edge, texture and detail information of the image, and avoid the target edge Halo artifact phenomenon, and more conducive to visual observation, to achieve a very good fusion effect

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