Reconstructing static scene viewed through smoke using video
Akos Kiss, Tamás Szirányi · 2011
In this paper we present a method for reconstructing static scene viewed through thick smoke using multiple images. Based on spatiotemporal statistical approach our method works well on noisy videos containing swirling smoke. We apply statistical analysis on regions of color input images, and show the way to reconstruct scene by transforming images to alter mean and deviation locally. We introduce a method to extract necessary parameters using multiple frames of a video. We verify our method with the widely used physical model of aerosols, highlighting some differences from removing haze and fog - a widely studied area. Furthermore, our approach eliminates the need for complex optimization, making real-time processing possible. Results show that our method is capable of reconstructing scene in challenging cases.