Experimental investigation of aliasing in the assessment of sampled images

Many visible and infrared sampled imaging systems suffer from moderate to severe amounts of aliasing. The problem arises because the large optical apertures required for sufficient light gathering ability result in large spatial cutoff frequencies. In consumer grade cameras, images are often undersampled by a factor of twenty times the suggested Nyquist rate. Most consumer cameras employ birefringent blur filters that purposely blur the image prior to detection to reduce Moiré artifacts produced by aliasing. In addition to the obvious Moiré artifacts, aliasing introduces other pixel level errors that can cause artificial jagged edges and erroneous intensity values. These types of errors have led some investigators to treat the aliased signal as noise in imaging system design and analysis. The importance of aliasing is dependent on the nature of the imagery and the definition of the assessment task. In this study, we employ a laboratory experiment to characterize the nature of aliasing noise for a variety of object classes. We aquire both raw and blurred imagery to explore the impact of pre-detection antialiasing. We also consider the post detection image restoration requirements to restore the in-band image blur produced by the anti-aliasing schemes.