Complex coal mine image defogging method based on improved generative adversarial network

Abstract

The invention discloses a complex coal mine image defogging method based on an improved generative adversarial network, and the method comprises a two-stage network: a combined defogging network based on a haze imaging model, and a refinement network based on the generative adversarial network. The first-stage learning is realized by directly embedding a haze imaging model into a network, so that the proposed method is ensured to strictly follow a physical scattering model for defogging. And for the second stage, a conditional generative adversarial network (GAN, Generative Advanced Network) is provided to recover background details which cannot be captured in the first stage, and the image artifacts introduced in the stage are corrected. The invention provides a novel channel attention network (CA, Channel Attention), which is inspired by the attention mechanism and is used for recovering a real and clear image from the output result of the first stage. In order to obtain a better result, a basic GAN formula is further modified, and perceptual fusion is introduced.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a channel attention mechanism and an image defogging method of an inception module. Background technique [0002] In the coal mine environment, the underground water vapor content is relatively sufficient and the relative humidity is relatively high. When there is a certain difference between the underground temperature and the air temperature above it, fog is easily formed. Fog is an extremely dangerous weather phenomenon. The effect of fog makes the computer imaging system unable to obtain clear images, resulting in blurred image content obtained by image acquisition equipment, decreased contrast, color distortion, and information loss. It will cause low atmospheric visibility and scene images. The phenomenon of degradation will seriously affect the coal mine construction operation, so there is a certain degree of safety hazard, which requires image defoggi...

AI Technical Summary

Problems solved by technology

The present invention proposes a complex sea-air scene image defogging method based on a generative confrontation network, which solves the above problems by designing a generative confrontation network, and at the same time solves the problems of color distortion and blurring after image defogging

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