Fuzzy rough sets hybrid scheme for motion and scene complexity adaptive deinterlacing
Image and Vision Computing
De-interlacing algorithm using spatial-temporal correlation-assisted motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
An MRF-based deinterlacing algorithm with exemplar-based refinement
IEEE Transactions on Image Processing
Detection of object motion regions in aerial image pairs with a multilayer Markovian model
IEEE Transactions on Image Processing
An adaptive motion-compensated approach for video deinterlacing
Multimedia Tools and Applications
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A lot of research has been conducted on motion-compensated (MC) de-interlacing, but there are very few publications that discuss the performances of de-interlacing quantatively. The various methods are compared through their performance on known video sequences. Linear system analysis of interlaced video and de-interlacer are proposed in . It is well established that the performance of the MC methods outperform the fixed or motion-adaptive methods when the motion vectors used are reliable and true to the scene content. Being an open-loop process the performance of the MC de-interlacers degrade drastically when there are motion vector errors. In this paper, a linear system analysis of MC video upconversion systems is presented and the effects of motion vector accuracy on system performance are analyzed. We investigate the various factors that contribute to the motion vector inaccuracy, such as incorrect motion modelling, acceleration between the frames, and insufficient interpolation kernel