Editing Halftone (section)

===Spatial and frequency filtering===

The main steps of the procedure are the removal of halftone patterns and reconstruction of tone changes. In the end, it may be necessary to recover details to improve image quality. There are many halftoning algorithms which can be mostly classified into the categories [[ordered dithering]], [[error diffusion]], and optimization-based methods. It is important to choose a proper descreening strategy since they generate different patterns and most of the inverse halftoning algorithms are designed for a particular type of pattern. Time is another selection criteria because many algorithms are iterative and therefore rather slow.

The most straightforward way to remove the halftone patterns is the application of a [[low-pass filter]] either in spatial or frequency domain. A simple example is a [[Gaussian filter]]. It discards the high-frequency information which blurs the image and simultaneously reduces the halftone pattern. This is similar to the blurring effect of our eyes when viewing a halftone image. In any case, it is important to pick a proper [[bandwidth (signal processing)|bandwidth]]. A too-limited bandwidth blurs edges out, while a high bandwidth produces a noisy image because it does not remove the pattern completely. Due to this trade-off, it is not able to reconstruct reasonable edge information.

Further improvements can be achieved with edge enhancement. Decomposing the halftone image into its [[wavelet transform|wavelet representation]] allows to pick information from different frequency bands.<ref>{{cite book|last1=Zixiang Xiong|last2=Orchard|first2=M.T.|last3=Ramchandran|first3=K.|title=Proceedings of 3rd IEEE International Conference on Image Processing |chapter=Inverse halftoning using wavelets |volume=1|pages=569–572|publisher=IEEE|doi=10.1109/icip.1996.559560|isbn=0-7803-3259-8|year=1996|s2cid=35950695}}</ref> Edges are usually consisting of highpass energy. By using the extracted highpass information, it is possible to treat areas around edges differently to emphasize them while keeping lowpass information among smooth regions.