A self-profiling image noise and edge enhancement filter
Radu Gheorghe, Andrei Tchouprakov, Mark Quadling · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
Threshold estimation in various image noise suppression and edge sharpening algorithms may still contain traces of subjective determination, with groups of subjects preferring more or less than optimal amounts of noise reduction and respectively edge enhancement. We propose in this paper a novel image noise reduction and edge enhancement technique that includes a profiling step for optimal noise threshold selection and resulting spatial frequency response (SFR). Our filter is implemented in the wavelet domain due to flexibility of spatially examining frequencies of interest. The method allows for selectively steering the algorithm to filter the low light 'chrominance noise' of certain hues in color filter array (CFA) cameras more so than others, and for building of a camera noise 'pseudo profile'.