The approach aims at enhancing the signal content of the original two-dimensional pattern by a comparison with a Poisson Statistics fluctuating background: the analyst must decide what values of the statistic correspond to better or worse levels of agreement with the hypothesis in question, defined as the probability to find signal data in the region of fluctuating data driven background. The latter one is obtained by smearing out the original data set, for instance by iteratively applying renormalization group transforms. Thus a cumulative distribution is obtained and regions where original data set values are higher are then promptly identified as signals.
Data-driven SNR improving in SAXS imaging
M Ladisa
2019
Abstract
The approach aims at enhancing the signal content of the original two-dimensional pattern by a comparison with a Poisson Statistics fluctuating background: the analyst must decide what values of the statistic correspond to better or worse levels of agreement with the hypothesis in question, defined as the probability to find signal data in the region of fluctuating data driven background. The latter one is obtained by smearing out the original data set, for instance by iteratively applying renormalization group transforms. Thus a cumulative distribution is obtained and regions where original data set values are higher are then promptly identified as signals.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
