Estimating Fog Parameters From an Image Sequence Using Non-Linear Optimisation

Yining Ding, Andrew M. Wallace, Sen Wang; Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024, pp. 1578-1586

Abstract


Given a sequence of images taken in foggy weather, we seek to estimate the atmospheric light and the scattering coefficient. These are key parameters to characterise the nature of the fog, to reconstruct a clear image (defogging), and to infer scene depth. Existing methods adopt a sequential estimation strategy which is prone to error propagation. In sharp contrast, we take a more systematic approach and jointly estimate these parameters by solving a unified non-linear optimisation problem. Experimental results show that the proposed method is superior to existing ones in terms of both estimation accuracy and precision. Our method further demonstrates how image defogging and depth estimation can be linked to a visual localisation system, contributing to more comprehensive and robust perception in fog.

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[bibtex]
@InProceedings{Ding_2024_WACV, author = {Ding, Yining and Wallace, Andrew M. and Wang, Sen}, title = {Estimating Fog Parameters From an Image Sequence Using Non-Linear Optimisation}, booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}, month = {January}, year = {2024}, pages = {1578-1586} }