Fast and robust video stabilisation with preserved intentional camera motion and smear removal for infrared video. Issue 2 (6th January 2020)

• Record Type: Journal Article
• Authors: Khare, Sudhir; Singh, Manvendra; Kaushik, Brajesh Kumar
• Is Part Of: IET image processing. Volume 14:Issue 2(2020)
• Page Start: 376
• Page End: 383
• Publication Date: 2020-01-06
• Subjects: image matching -- video signal processing -- image motion analysis -- motion estimation -- image sequences -- feature extraction -- cameras -- video surveillance; infrared domain -- complete visual sequences -- pitch dark night conditions -- thermal camera -- output video -- visual quality -- unintentional camera motion -- unwanted motions -- smear removal -- intentional motion -- robust features -- stabilised output videos -- robust video stabilisation -- infrared video -- border military surveillance -- intentional camera motion; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2019.0764
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : Border military surveillance is one of the demanding and challenging tasks for any nation. Thermal (infrared) camera, which works on the infrared domain, provides complete visual sequences even in pitch dark night conditions. When the video is recorded from a thermal camera mounted on a vehicle, the output video is unstabilised with poor visual quality due to unintentional camera motion. These unwanted motions also introduce smear. Furthermore, there may be situations when a camera is moved intentionally to capture target. This study proposes a fast and robust algorithm for auto stabilisation of videos with smear removal while keeping the intentional motion of camera. This algorithm is developed under the framework of speeded up robust features matching. The proposed algorithm is capable of correcting both motions, i.e. translation as well as rotational. Quality improvement of up to 21 dB is achieved in the stabilised output videos.