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ACIVS
2006
Springer

Greyscale Image Interpolation Using Mathematical Morphology

14 years 6 months ago
Greyscale Image Interpolation Using Mathematical Morphology
When magnifying a bitmapped image, we want to increase the number of pixels it covers, allowing for finer details in the image, which are not visible in the original image. Simple interpolation techniques are not suitable because they introduce jagged edges, also called “jaggies”. Earlier we proposed the “mmint” magnification method (for integer scaling factors), which avoids jaggies. It is based on mathematical morphology. The algorithm detects jaggies in magnified binary images (using pixel replication) and removes them, making the edges smoother. This is done by replacing the value of specific pixels. In this paper, we extend the binary mmint to greyscale images. The pixels are locally binarized so that the same morphological techniques can be applied as for mmint. We take care of the more difficult replacement of pixel values, because several grey values can be part of a jaggy. We then discuss the visual results of the new greyscale method.
Alessandro Ledda, Hiêp Quang Luong, Wilfried
Added 13 Jun 2010
Updated 13 Jun 2010
Type Conference
Year 2006
Where ACIVS
Authors Alessandro Ledda, Hiêp Quang Luong, Wilfried Philips, Valérie De Witte, Etienne E. Kerre
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