Abstract
Machine design of a signal or image operator involves estimating the optimal filter from sample data. The optimal filter is the best filter, relative to the error measure used; however, owing to design error, the designed filter might not perform well. In general it is suboptimal. The envelope constraint involves using two humanly designed filters that form a lower and upper bound for the designed operator. The method has been employed for binary operators. This paper considers envelope design for gray-scale filters, in particular, aperture filters. Some basic theoretical properties are stated, including optimality of the design method relative to the constraint imposed by the envelope. Examples are given for noise reduction and de-blurring.
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Brun, M., Hirata, R., Barrera, J. et al. Nonlinear Filter Design Using Envelopes. Journal of Mathematical Imaging and Vision 21, 81–97 (2004). https://doi.org/10.1023/B:JMIV.0000026558.10581.e6
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DOI: https://doi.org/10.1023/B:JMIV.0000026558.10581.e6