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Proceedings Paper

Noise estimation for color visualization of multispectral images
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Paper Abstract

We study a technique for improving visualization quality of noisy multispectral images. Contrast form visualization approach is considered, which guarantees a non-zero contrast in the output image when there is a difference between the spectra of the object and the background in the input image. The improvement is based on channel weighting according to estimation of the noise level. We show this approach to reduce noise in color visualization of real multispectral images. The low-noise visualizations are demonstrated to be more comprehensive to a human on examples from a publicly available dataset of Earth surface images. Noise variance estimation needed for weighting uses the method proposed earlier by the authors. The validation dataset consists of publicly available images of Earth surface.

Paper Details

Date Published: 8 February 2017
PDF: 5 pages
Proc. SPIE 10253, 2016 International Conference on Robotics and Machine Vision, 1025307 (8 February 2017); doi: 10.1117/12.2266352
Show Author Affiliations
D. Sidorchuk, Institute for Information Transmission Problems (Russian Federation)
I. Konovalenko, Institute for Information Transmission Problems (Russian Federation)
S. Gladilin, Institute for Information Transmission Problems (Russian Federation)
Y. Maximov, Institute for Information Transmission Problems (Russian Federation)


Published in SPIE Proceedings Vol. 10253:
2016 International Conference on Robotics and Machine Vision
Alexander V. Bernstein; Adrian Olaru; Jianhong Zhou, Editor(s)

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