Discriminating smooth image regions from areas in which significant signal activity occurs is a widely studied subject and is important in low level image processing as well as computer vision applications. In this paper we present a novel method for estimating signal activity in an image directly in the CFA (Color Filter Array) Bayer raw domain. The solution is robust against noise in that it utilizes low level noise characterization of the image sensor to automatically compensate for high noise levels that contaminate the image signal.

Signal Activity Estimation with Built-in Noise Management in Raw Digital Images

BATTIATO, SEBASTIANO;
2013-01-01

Abstract

Discriminating smooth image regions from areas in which significant signal activity occurs is a widely studied subject and is important in low level image processing as well as computer vision applications. In this paper we present a novel method for estimating signal activity in an image directly in the CFA (Color Filter Array) Bayer raw domain. The solution is robust against noise in that it utilizes low level noise characterization of the image sensor to automatically compensate for high noise levels that contaminate the image signal.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/87597
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