Video Smoke Removal Based on Smoke Imaging Model and Space-Time Pixel Compensation

Conference paper

DOI: 10.1007/978-3-319-56010-6_4

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10213)
Cite this paper as:
Yamaguchi S., Hirai K., Horiuchi T. (2017) Video Smoke Removal Based on Smoke Imaging Model and Space-Time Pixel Compensation. In: Bianco S., Schettini R., Trémeau A., Tominaga S. (eds) Computational Color Imaging. CCIW 2017. Lecture Notes in Computer Science, vol 10213. Springer, Cham

Abstract

This paper presents a novel video smoke removal method based on a smoke imaging model and space-time pixel compensation. First, we develop an optical imaging model for natural scenes that contain smoke. Then, we remove the smoke in a video, frame-by-frame, based on the smoke imaging model and conventional dehazing approaches. Next, we align the smoke-removed frames using corresponding pixels. To obtain the corresponding pixels, we use SIFT and color features with distance constraints. Finally, to reproduce clear video appearance, we compensate pixel values by utilizing the space-time weightings of the corresponding pixels between the smoke-removed frames. Validation experiments show our method can provide effective smoke removal resulting in dynamic scenes.

Keywords

Smoke removal Dehazing Dark Channel Prior Smoke imaging model Pixel compensation 

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Graduate School of Advanced Integration ScienceChiba UniversityChibaJapan

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