Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Digital video processing
De-Interlacing: A Key Technology for Scan Rate Conversion
De-Interlacing: A Key Technology for Scan Rate Conversion
Video Processing and Communications
Video Processing and Communications
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Deinterlacing by successive approximation
IEEE Transactions on Image Processing
Partial Differential Equations for Zooming, Deinterlacing and Dejittering
International Journal of Computer Vision
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We propose a new way of deinterlacing using a total variation scheme. Starting by the Bayesian inference formulation of total variation we do MAP by rewriting the problem into PDEs that can be solved by simple numerical schemes. Normally deinterlacing schemes are developed ad hoc with online hardware implementation directly at eye, sometimes with some frequency analysis as only theoretical base. Our belief is that mathematically well based image models are needed to do optimal deinterlacing and by our work presented here, we hope to prove it. Comparing the output of our scheme with those of ten known deinterlacing schemes shows very promising results.