| With the development of industry in the country,emissions of various gases have resulted in hazy weather,which has degraded the quality of images or videos captured outdoors,which has seriously affected the sharpness of images and thus affected the extraction of image feature values.Reduce the application value of the image.Therefore,it is of great significance to defogging the fog image.In this dissertation,the image defogging algorithm based on histogram equalization,Retinex and dark channel priority is simulated,the related parameters are used to study the image after defogging,and the advantages and disadvantages of various defogging algorithms under certain conditions are summarized.A quarter-division method is used to obtain the atmospheric light value of the fog image so that the obtained atmospheric light value is closer to the true value.Then,based on the physical model of the atmosphere and the dark channel principle,the transmission rate that satisfies the conditions is determined,and the excessive enhancement of the image is prevented by increasing the constraint condition of the transmittance,and an improved dark channel defogging algorithm is formed,effectively overcoming the dark channel priority image.The defogging algorithm deals with the distortion of the sky area appearing in the image,and uses MATLAB to perform simulation experiments to prove the effectiveness of the improved algorithm.At the same time,the video defogging algorithm is studied on the basis of image defogging,and the improved image dehazing algorithm is applied to the video dehazing algorithm to further verify the effectiveness of the improved algorithm.Finally,the dehazing system is designed and implemented using the improved dehazing algorithm.The results show that the improved dehazing algorithm effectively overcomes the disadvantages of the dark channel dehazing algorithm for improper handling of sky areas in the image and has certain application value in image dehazing. |
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