Infrared and visible image fusion method based on generated countermeasure network

Abstract

The invention discloses an infrared and visible light image fusion method based on a generation countermeasure network, the invention is characterized in that: a generating antagonistic network is established; the generating antagonistic network comprises a generator and a decider; the generator and the decider are arranged as a convolution neural network; and the fusion characteristics and the fusion rules are automatically learned in the process of training the convolution neural network; The infrared image and the visible image are simultaneously input to generate the generator in the countermeasure network. The generator performs image fusion operation and outputs the final fusion image. The invention breaks through the limitation of fusion features and rules of manual design, the fused image generated by the invention can well keep the basic radiation information of the infrared image and has abundant texture information, meanwhile, the visual effect of the fused image is good andthe saliency of the target is high.

Description

technical field [0001] The present invention relates to the technical field of infrared image fusion, in particular, the present invention relates to a technical proposal for fusion of infrared and visible light images based on a generative confrontation network. Background technique [0002] The infrared imaging system has strong anti-interference ability, good concealment performance, strong atmospheric penetration ability, obvious target, and can adapt to many special occasions. However, due to the characteristics of the infrared detector itself, such as high sensitivity and large dynamic range, as well as various noise interference in the complex working environment, the infrared image shows the characteristics of high background and low contrast. The specific performance is that the imaging scene only accounts for a small part of the dynamic range of the entire infrared imaging system, and the image contrast is poor and blurred. On the contrary, the visible light image...

AI Technical Summary

Problems solved by technology

However, these methods all use the same strategy to select the same salient features in the infrared image and the visible light image for fusion, so that the target that was originally salient in the infrared image is no longer salient in the visible light image.

At the same time, these methods have to manually design fusion features and fusion rules, making it difficult to make new breakthroughs in the field of infrared and visible light images.

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