Polarimetric dehazing is an effective way to enhance the quality of images captured in foggy weather.However,images of essential polarization parameters are vulnerable to noise,and the brightness of dehazed images is ...Polarimetric dehazing is an effective way to enhance the quality of images captured in foggy weather.However,images of essential polarization parameters are vulnerable to noise,and the brightness of dehazed images is usually unstable due to different environmental illuminations.These two weaknesses reveal that current polarimetric dehazing algorithms are not robust enough to deal with different scenarios.This paper proposes a novel,to our knowledge,and robust polarimetric dehazing algorithm to enhance the quality of hazy images,where a low-rank approximation method is used to obtain low-noise polarization parameter images.Besides,in order to improve the brightness stability of the dehazed image and thus keep the image have more details within the standard dynamic range,this study proposes a multiple virtual-exposure fusion(MVEF)scheme to process the dehazed image(usually having a high dynamic range)obtained through polarimetric dehazing.Comparative experiments show that the proposed dehazing algorithm is robust and effective,which can significantly improve overall quality of hazy images captured under different environments.展开更多
A novel polarimetric dehazing method is proposed based on three linear polarization images(0°,45°,and 90°).The polarization orientation angle of the light scattered by the haze particles is introduced i...A novel polarimetric dehazing method is proposed based on three linear polarization images(0°,45°,and 90°).The polarization orientation angle of the light scattered by the haze particles is introduced in the algorithm.No additional image-processing algorithm is needed in the postprocessing.It is found that the dehazed image suffers from little noise and the details of the objects close to the observer can be preserved well.In addition,this algorithm is also proved to be useful for preserving image colors.Experimental results demonstrate that such an algorithm has some universality in handling all kinds of haze.We think that this robust algorithm might be very suitable for real-time dehazing.展开更多
Traditional one-way imaging methods become invalid when a target object is completely hidden behind scattering media. In this case, it has been much more challenging, since the light wave is distorted twice.To solve t...Traditional one-way imaging methods become invalid when a target object is completely hidden behind scattering media. In this case, it has been much more challenging, since the light wave is distorted twice.To solve this problem, we propose an imaging method, so-called round-trip imaging, based on the optical transmission matrix of the scattering medium. We show that the object can be recovered directly from the distorted output wave, where no scanning is required during the imaging process. We predict that this method might improve the imaging speed and have potential application for real-time imaging.展开更多
基金Science and Technology Development Funds of Shaanxi Province(2024QCY-KXJ-179)Natural Science Foundation of Shaanxi Province(2021JM-204,2022JQ-612)Xi'an Scientific and Technological Projects(2020KJRC0013)。
文摘Polarimetric dehazing is an effective way to enhance the quality of images captured in foggy weather.However,images of essential polarization parameters are vulnerable to noise,and the brightness of dehazed images is usually unstable due to different environmental illuminations.These two weaknesses reveal that current polarimetric dehazing algorithms are not robust enough to deal with different scenarios.This paper proposes a novel,to our knowledge,and robust polarimetric dehazing algorithm to enhance the quality of hazy images,where a low-rank approximation method is used to obtain low-noise polarization parameter images.Besides,in order to improve the brightness stability of the dehazed image and thus keep the image have more details within the standard dynamic range,this study proposes a multiple virtual-exposure fusion(MVEF)scheme to process the dehazed image(usually having a high dynamic range)obtained through polarimetric dehazing.Comparative experiments show that the proposed dehazing algorithm is robust and effective,which can significantly improve overall quality of hazy images captured under different environments.
基金This work was supported in part by the National Natural Science Foundation of China under Grants 61275149 and 51207159the Advanced Programs of Technological Activities for Overseas Scholars.
文摘A novel polarimetric dehazing method is proposed based on three linear polarization images(0°,45°,and 90°).The polarization orientation angle of the light scattered by the haze particles is introduced in the algorithm.No additional image-processing algorithm is needed in the postprocessing.It is found that the dehazed image suffers from little noise and the details of the objects close to the observer can be preserved well.In addition,this algorithm is also proved to be useful for preserving image colors.Experimental results demonstrate that such an algorithm has some universality in handling all kinds of haze.We think that this robust algorithm might be very suitable for real-time dehazing.
基金supported by the National Natural Science Foundation of China(Nos.61535015,61275149,and 61275086)the Special Scientific Research Plan from Education Department of Shaanxi Provincial Government(No.16JK1083)
文摘Traditional one-way imaging methods become invalid when a target object is completely hidden behind scattering media. In this case, it has been much more challenging, since the light wave is distorted twice.To solve this problem, we propose an imaging method, so-called round-trip imaging, based on the optical transmission matrix of the scattering medium. We show that the object can be recovered directly from the distorted output wave, where no scanning is required during the imaging process. We predict that this method might improve the imaging speed and have potential application for real-time imaging.
