Removal of specular reflections from image sequences using feature correspondences
M. Z. Abbas Shah, Syed. and Marshall, Stephen and Murray, Paul (2017) Removal of specular reflections from image sequences using feature correspondences. Machine Vision and Applications, 28 (3). pp. 409-420. ISSN 0932-8092 (https://doi.org/10.1007/s00138-017-0826-6)
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Abstract
The presence of specular highlights can hide underlying features of a scene within an image and can be problematic in many application scenarios. In particular, this poses a significant challenge for applications where image stitching is used to create a single static image of a scene from inspection footage of pipes, gas tubes, train tracks and concrete structures. Furthermore, they can hide small defects in the images causing them to be missed during inspection. We present a method which exploits additional information in neighbouring frames from video footage to reduce specularity from each frame. The technique first automatically determines frames which contain overlapping regions before the relationship that exists between them is exploited in order to suppress the effects of specular reflections. This results in an image that is free from specular highlights provided there is at least one frame present in the sequence where a given pixel is present in a diffuse form. The method is shown to work well on greyscale as well as colour images and effectively reduces specularity and significantly improves the quality of the stitched image, even in the presence of noise. While applied to the challenge of reducing specularity in inspection videos, the method improves upon the state-of-the-art in specularity removal, and, its applications are wider ranging as a general purpose pre-processing tool.
ORCID iDs
M. Z. Abbas Shah, Syed., Marshall, Stephen ORCID: https://orcid.org/0000-0001-7079-5628 and Murray, Paul ORCID: https://orcid.org/0000-0002-6980-9276;-
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Item type: Article ID code: 59688 Dates: DateEvent26 April 2017Published18 February 2017Published Online2 February 2017AcceptedNotes: The final publication is available at Springer via http://dx.doi.org/10.1007/s00138-017-0826-6 Subjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset Management
Strategic Research Themes > Measurement Science and Enabling TechnologiesDepositing user: Pure Administrator Date deposited: 02 Feb 2017 16:31 Last modified: 22 Dec 2024 01:19 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/59688