When scanning a document that is printed on both sides, the image on the reverse can show through with high luminance.
We propose an adaptive method of removing show-through artifacts based on histogram analysis. Instead of attempting
to measure the physical parameters of the paper and the scanning system, or making multiple scans, we analyze the color
distribution to remove unwanted artifacts, using an image of the front of the document alone. First, we accumulate
histogram information to find the lightness distribution of pixels in the scanned image. Using this data, we set thresholds
on both luminance and chrominance to determine candidate regions of show-through. Finally, we classify these regions
into foreground and background of the image on the front of the paper, and show-through from the back. The
background and show-through regions become candidates for erasure, and they are adaptively updated as the process
proceeds. This approach preserves the chrominance of the image on the front of the papers without introducing artifacts.
It does not make the whole image brighter, which is what happens when a fixed threshold is used to remove show-through.
Present paper generally relates to content-aware image resizing and image inscribing into particular predetermined areas.
The problem consists in transformation of the image to a new size with or without modification of aspect ratio in a
manner that preserves the recognizability and proportions of the important features of the image. Most close solutions
presented in prior art cover along with standard image linear scaling, including down-sampling and up-sampling, image
cropping, image retargeting, seam carving and some special image manipulations which similar to some kind of image
retouching. Present approach provides a method for digital image retargeting by means of erasing or addition of less
significant image pixels. The defined above retargeting approach can be easily used for image shrinking easily. However,
for image enlargement there are some limitations as a stretching artifact. History map with relaxation is introduced to
avoid such drawback and overcome some known limits of retargeting. In proposed approach means for important objects
preservation are taken into account. It allows significant improvement of resulting quality of retargeting. Retargeting
applications for different devices such as display, copier, facsimile and photo-printer are described as well.