Abstract
A fuzzy if-then rule-based intra-field deinterlacing method using geometric
duality is presented in this paper. The proposed method is a content-based hybrid scheme
switching between the well-known edge-based linear average method and the proposed
geometric duality-based deinterlacing method. Conventional deinterlacing methods usually
employ edge-based interpolation techniques within pixel-based estimations. However, they
are somewhat sensitive to noise and intensity variations in the image. Moreover, their
performance is visually unacceptable due to their failure to estimate edge direction. To
reduce this sensitivity, the proposed algorithm investigates features from
low-resolution images, and applies them to high-resolution images to calculate the
missing pixels. We analyzed properties of the missing pixels and modeled them using
geometric regularity. Depending on the features of the region, the missing pixels were
interpolated in different ways. The proposed algorithm is computationally feasible and
promises to be a good candidate for a low-cost hardware interpolator.
© 2010 IEEE
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