Image defogging method, device, electronic equipment and medium

Abstract

Embodiments of the present disclosure provide an image defogging method, device, electronic equipment, and medium. The method includes: preprocessing the image to be processed to obtain a preprocessing vector; inputting the preprocessing vector into the convolution layer and the minimum pooling layer of the neural network model to obtain at least two intermediate vectors, and splicing the at least two intermediate vectors Finally, input a convolutional layer to obtain the target vector; the neural network model includes at least two convolutional layers and at least one minimum pooling layer, and the target vector matches the vector of the pre-processing vector; activates the target vector and the pre-processing vector , to get the image after dehazing. Embodiments of the present disclosure can perform effective dehazing processing on images.

Description

technical field [0001] The present disclosure relates to the field of image defogging, and in particular, the present disclosure relates to an image defogging method, device, electronic equipment, and medium. Background technique [0002] In the case of bad weather conditions, the images taken outdoors are often significantly degraded by the particles suspended in the air, resulting in a series of problems such as a decrease in image contrast and color distortion. Scattered by fog, haze, dust, etc. in the air, so it is the scattered light that finally reaches the camera. Haze images are usually composed of directly attenuated and scattered atmospheric light, the direct attenuation is the light intensity received by the camera after reflection and attenuation on the surface of the object, and the scattered atmospheric light is the scattered atmospheric light received by the camera. Image defogging algorithm has gradually become a research hotspot in military, aerospace, tran...

AI Technical Summary

Problems solved by technology

[0003] At present, traditional image defogging methods rely on its artificial features to calculate depth or transmittance. However, these artificial features have their own limitations, so that the image defogging effect is limited and satisfactory images cannot be obtained.

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