Abstract
This chapter investigates the mean squared error as a criterion for selecting an optimal soft threshold. In applications like image processing, it is often objected that this expression of the error does not always correspond to a more subjective experience of quality. Our visual system, for instance, is much more sensitive to contrast than is expressed by a mean squared error. Nevertheless, even in the image processing world, definitions of signal-to-noise ratio, based on mean squared errors, are commonly used.
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© 2001 Springer Science+Business Media New York
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Jansen, M. (2001). The minimum mean squared error threshold. In: Noise Reduction by Wavelet Thresholding. Lecture Notes in Statistics, vol 161. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-0145-5_3
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DOI: https://doi.org/10.1007/978-1-4613-0145-5_3
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-95244-4
Online ISBN: 978-1-4613-0145-5
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