Unmanned aerial vehicle aerial image defogging algorithm based on dark channel

Abstract

The present invention discloses an unmanned aerial vehicle aerial image defogging algorithm based on a dark channel. The algorithm comprises the steps of: obtaining a dark channel image according to acolor foggy image, obtaining a global atmospheric light composition A according to the dark channel image, obtaining a coarse-transmissivity graph according to the dark channel image, performing downsampling of the coarse-transmissivity graph, performing guidance filtering, performing upsampling to obtain a fine-transmissivity graph, obtaining an initial defogging image according to the fine-transmissivity graph and the global atmospheric light composition A, and employing restriction contrast adaptive histogram equalization to perform local contrast enhancement of the initial defogging imageto solve the problems that the image is dark and highlights the local information of the original image after defogging of the dark channel and to be used for later image processing work. The unmanned aerial vehicle aerial image defogging algorithm is especially suitable for defogging operation of high-resolution foggy images shot by the unmanned aerial vehicle, can obtain more image detail points of the unmanned aerial vehicle while rapidly removing the fog images of the images of the unmanned aerial vehicle, can simplify computing and has good robustness.

Description

technical field [0001] The invention belongs to the technical field of image defogging of dark channel prior models, and in particular relates to a dark channel-based algorithm for defogging aerial images of unmanned aerial vehicles. Background technique [0002] In recent years, with the rapid development of UAV technology, its military and civilian applications continue to expand. The role of unmanned aerial vehicles in the low-altitude detection system is irreplaceable. Its operation and maintenance are simple, its cost is low, its movements are flexible and it can continue to work. It is not limited to the tasks performed by manned aircraft. Extensive, such as natural disaster area monitoring, public safety, air rescue command, water conservancy, mineral resource exploration. UAV is a micro-remote sensing technology for aerial remote sensing platform. The remote sensing sensor obtains information through the UAV, processes the image information with a computer, and then...

AI Technical Summary

Problems solved by technology

Among them, the method based on depth information can significantly enhance the contrast and visual effects, but requires a certain degree of user interaction, and it is difficult to achieve real-time automatic processing.

The premise of the defogging method based on atmospheric light polarization is easy to implement, and it can guarantee real-time defogging processing of videos to a certain extent, but the effect is poor when the fog concentration is high, and it cannot be automatically processed for a single image

The image defogging method based on the dark channel can handle a single image and an image with a large change in bit depth. The size of the dark channel filter window needs to be manually set, and the size of the dark channel filter window directly affects the projection rate map. calculation, and because a large amount of calculation is required when guiding the filter, it is difficult to achieve real-time processing, especially because the resolution of the UAV image itself is too high, real-time processing is more difficult

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