Noise estimation for color visualization of multispectral images

D. Sidorchuk; I. Konovalenko; S. Gladilin; Y. Maximov

doi:10.1117/12.2266352

8 February 2017 Noise estimation for color visualization of multispectral images

D. Sidorchuk, I. Konovalenko, S. Gladilin, Y. Maximov

Proceedings Volume 10253, 2016 International Conference on Robotics and Machine Vision; 1025307 (2017) https://doi.org/10.1117/12.2266352
Event: 2016 International Conference on Robotics and Machine Vision, 2016, Moscow, Russia

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.

Citation Download Citation

D. Sidorchuk, I. Konovalenko, S. Gladilin, and Y. Maximov "Noise estimation for color visualization of multispectral images", Proc. SPIE 10253, 2016 International Conference on Robotics and Machine Vision, 1025307 (8 February 2017); https://doi.org/10.1117/12.2266352

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