Patent ID: 7876975
Filing Date: 2011-01-25
Classification: G06T,G10L

Abstract:
1. A method performed by a signal processing device for deriving noise statistical properties (NSP) for a signal (S), comprising: (a) providing a distorted signal (DS) originating from an underlying signal (S) to be evaluated; (b) deriving distorted noise statistical properties (DNSP) from said distorted signal (DS); (c) subjecting, using the signal processing device, said distorted noise statistical properties (DNSP) to a deconvolution/inversion process with respect to a respective noise model (NM) for said underlying signal (S) to be evaluated; and (d) deriving undistorted noise statistical properties as said noise statistical properties (NSP) for said underlying undistorted signal (S), wherein said step of subjecting (c) said distorted noise statistical properties to a deconvolution/inversion process is performed at least in part iteratively and said step of subjecting (c) includes (c1) deriving or measuring at least one of the group consisting of a mean value and a variance value from said distorted signal as a distorted mean value and as a distorted variance value, respectively, (c2) initially setting and using measured mean value and measured variance value from step (c1) as starting iteration values and as intermediate iteration values, (c3) evaluating one of a) said variance by numerical inversion for a next iteration step based on said intermediate iteration values for said mean, and b) said mean by numerical inversion for a next iteration step based on said intermediate iteration values for said variance, and in response to evaluating said variance, taking said mean as a new respective intermediate iteration value for said variance and, in response to evaluating said mean, taking said variance as a new respective intermediate iteration value for said mean, (c4) evaluating one of a) said variance by numerical inversion for a next iteration step based on said intermediate iteration values for said mean, and b) said mean by numerical inversion for a next iteration step based on said intermediate iteration values for said variance, which was not evaluated in step (c3), and in response to evaluating said variance in step (c4), taking said mean as a new respective intermediate iteration value for said variance and, in response to evaluating said mean in step (c4), taking said variance as a new respective intermediate iteration value for said mean, (c5) repeating at least one of said steps (c3) and (c4) for the next iteration step until given stopping criteria are fulfilled, and (c6) taking as noise statistical data (NSD), or as a part or a pre-form thereof, recently evaluated and calculated iteration values for said variance and for said mean, after stopping the iteration.