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Filtering Periodic Noise: Removal of Interference and Halftone Patterns
Periodic noise, arising from vibration, electronic interference, halftone printing, fluorescent lighting, or other causes is difficult or impossible to remove with neighborhood operations in the spatial or pixel domain, because it extends throughout the image. However, transforming the image to the Fourier or frequency domain often facilitates its removal. This interactive tutorial illustrates the removal of electronic interference and halftone patterns. The Fourier transform power spectrum of the noisy image shows spikes (bright points indicating specific noise frequencies). Creating a mask to remove those spikes may be done either manually or using processing tools that will be introduced later on, applied to the image of the power spectrum itself. Once the spikes are removed, transforming the image back to the pixel domain recovers the image with the noise suppressed or removed.
The tutorial initializes with a randomly selected specimen appearing in the Specimen Image window. The Choose A Specimen pull-down menu provides a selection of specimen images, in addition to the initial randomly chosen one. The radio buttons show the Original image, the Fourier transform Power Spectrum, the Mask that can remove the spikes due to the periodic noise, the Masked Power Spectrum with those spikes removed, and the Filtered Image after an inverse Fourier transform is applied.
Contributing Authors
John C. Russ - Materials Science and Engineering Dept., North Carolina State University, Raleigh, North Carolina, 27695.
Matthew Parry-Hill, and Michael W. Davidson - National High Magnetic Field Laboratory, 1800 East Paul Dirac Dr., The Florida State University, Tallahassee, Florida, 32310.
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