Noisy image processing using the independent component analysis algorithm AMUSE
نویسندگان
چکیده
In this article we investigate the performance of the ICA algorithm AMUSE when applied to images contaminated by noise. The classes of noise we are using have gaussian, multiplicative and impulsive distributions. We find that AMUSE copes surprisingly well with the different types of noise, including multiplicative noise.
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