Image defogging method and device

Abstract

The invention discloses an image defogging method and an image defogging device. The image defogging device comprises a dark channel calculation module, a histogram statistical module, an ambient light calculation module, a transmissivity calculation module, a storage module, a transmissivity selection module, a filtering module and a defogging processing module. The image defogging method comprises the steps of: dividing an image into a plurality of blocks; calculating dark channel values of each block in RGB components; counting histograms; calculating an ambient light value according to the histograms; calculating transmissivities in small, medium and large regions of three types; performing filtering treatment; and then performing defogging treatment by using a dark channel apriori algorithm model, so as to obtain image data after defogging. The image defogging method and the image defogging device perform optimization processing on parameters such as transmissivities and ambient light on the basis of the existing dark channel apriori algorithm model, so that the block effect and fringe effect of the image are eliminated, and the definition of the defogged image after restoration is high.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an image defogging method and device. Background technique [0002] With the development of digital image processing technology and VLSI, high resolution and high processing speed have become the development trend of video image technology. High-definition and high-quality images play a vital role in traffic monitoring, information science, and military fields. However, in fields such as outdoor traffic monitoring, the camera system is often affected by bad weather, and weather such as fog, haze, rain and snow directly reduces the clarity of the image. Therefore, it is particularly important to perform dehazing processing on video images in hazy weather. [0003] In the prior art, the processing of foggy images mainly focuses on the algorithm level of software development on the PC platform. Although these algorithms can achieve the purpose of defogging, becau...

AI Technical Summary

Problems solved by technology

Although these algorithms can achieve the purpose of defogging, because they are all software processing, they take a long time and cannot meet the high-speed and high-quality requirements of real-time monitoring chips such as ISP ((Image Signal Processing, Image Signal Processing)

Although some scholars have tried to realize the dehazing algorithm in FPGA (Field-Programmable Gate Array, Field Programmable Gate Array) and other hardware, they have degraded their own dehazing algorithm. Fog effects are bound to be affected

[0004] The defogging algorithm based on dark channel prior is recognized as the most effective and general algorithm, but most of the defogging methods and devices based on this algorithm model also have the problem of image block effect and edge effect, making The image transition is not smooth, and the quality of the restored defogged image cannot meet high requirements

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