We propose the technique of improving multispectral local contrast preserving visualization in noisy environment. The
technique is based on weighting of image bands according to estimations of their noise level. We consider two approaches
to weighting coef cients calculation: the min/max autocorrelation factors (MAF) method and the new method that considers
each channel as a realization of a parameterized gaussian process. Likelihood maximization gives the parameter values
which are used to estimate noise. Validity of the ordering given by both methods is verified using manually marked
multispectral dataset. We also show examples of visualization improvement obtained by bands weighting. The dataset used
consists of publicly available real multispectral images.
Key words:
multispectral images, multispectral visualization, noise estimation, local contrast preserving
Cite:
Sidorchuk D. S., Konovalenko I. A., Gladilin S. A., Maximov Y. I.
Otsenka shumnosti kanalov v zadache vizualizatsii multispektralnykh izobrazhenii
[Noise estimation for multispectral visualization].
Sensornye sistemy [Sensory systems].
2016.
V. 30(4).
P. 344-350 (in Russian).
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