New Model And Algorithm For Adaptive Color Image Defogging

Various particles suspended in the atmosphere can absorb,scatter,and refract light,resulting in blurred vision,poor visibility,and low image clarity.With the increasing haze problem,the research of image defogging becomes more and more important in image processing technology.In recent years,research hotspots at home and abroad have been to reduce or even eliminate the influence of fog on the scene in the image,so as to achieve the definition of foggy images.However,the existing defogging algorithm still has a series of deficiencies in image defogging.The lack of detailed information,low atmospheric light intensity estimation,poor defogging effect in the sky area and poor adaptive defogging effect have become bottlenecks affecting image clarity.In this paper,based on the dark channel prior theory,a new model and a new algorithm for parameter-driven image defogging are proposed.The algorithm mainly includes the following research contents: First,a bright channel prior model corresponding to the dark channel prior model is introduced.Based on this,the dark channel prior model and the bright channel prior model are linearly weighted with parameters to adaptively calculate the atmospheric light intensity.The model is based on the evaluation of objective indicators of image quality,and can adaptively obtain parameters corresponding to atmospheric light intensity values.Finally,a new parameter-driven image defogging algorithm is proposed based on the new model.The simulation results show that the proposed parameter-driven image defogging algorithm improves the detail information and atmospheric light intensity compared with the existing defogging algorithm.At the same time,the objective quality evaluation index of image quality verifies that the new image defogging algorithm driven by this parameter has a good application effect in foggy scenes.In order to further improve the application effect of the parameter-driven image defogging algorithm proposed in this paper,image processing techniques such as image segmentation and image fusion are also applied to image defogging.Based on the new model and new algorithm of parameter-driven color image defogging,the specific scheme is to propose a new image defogging algorithm for sky region segmentation correction.The research contents of the new algorithm mainly includes: First,the sky region portion is segmented by the SLIC image segmentation algorithm.Then,a new sky area correction model based on the weighted average fusion COPLIP model and the MSR model is proposed to process the segmented sky region.Finally,the final defogged image is obtained by image fusion technology.The new model and new algorithm of adaptive color image defogging proposed in this paper have achieved some optimization results in image defogging,and the deviation of defogging in sky region has been corrected to some extent.This innovative adaptive color image defogging algorithm and ideas have broad application prospects.