Rapid Imaging Polarization Detector And Foggy Image–sharpening Method

Under haze weather,as the target light is scattered by tiny particles in the air and reflected into the imaging equipment,the image quality obtained by the imaging equipment is greatly reduced,which has a great impact on military reconnaissance,port logistics,aircraft take-off and landing,and other fields.It is of great significance to study the method of foggy image – sharpening.Polarized light in the target region can provide more abundant information of the target,and the influence of weather factors such as haze on image quality can be eliminated by making full use the polarization property.For solving the above problems,based on the principle of stokes vector detection,a fast imaging polarization detector is designed to provide accurate image data for the sharpening method.The haze image is clearly processed by using the polarization image obtained by the detector combined with the defogging algorithm.The main work are as follows:(1)Based on the atmospheric scattering model,the theory of polarized light detection is combined with the principle of stokes vector detection.The polarized light is described by mathematical model,and the polarization image clarity model is established,which lays the foundation for the establishment of the de-fogging algorithm.(2)Based on the principle of stokes vector detection of light,the traditional mechanical rotating polarization detector has been improved,and the rapid imaging polarization detector has been designed and implemented.The imaging rate has been improved,and the problems of large volume,low imaging rate and poor spatiotemporal synchronism of the traditional mechanical rotating polarization imaging device have been removed,which can provide reliable image data for the subsequent clarity algorithm.(3)Based on the polarization de-hazing model,a polarization image de-fogging method using the histogram distribution of the distinction between the imaging of light and dark channels is proposed.The prior theory of dark channel is combined with the local variance of the image to accurately estimate the infinite point,and eliminate the random error caused by the manual selection of the infinite point;the histogram of the distinction between the bright channel image and the dark channel image of the image is adopted to calculat the polarization of atmospheric light,which transform the polarization of atmospheric ligh from global quantification to a local variable.(4)Based on the objective evaluation criteria,the de-fogging effect of the proposed algorithm is evaluated through experiments,and compared with other algorithms.The results shows that the proposed algorithm is better and more applicable in improving the quality of fog images.