An inpainting-based deinterlacing method
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Updated: Jul 11, 2026

Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro
Published on: December 3, 2018
Coloma Ballester1, Marcelo Bertalmío, Vicent Caselles
1Departament de Tecnologia, Universitat Pompeu Fabra, Barcelona, Spain. coloma.ballester@upf.edu
Abstract:
Video is usually acquired in interlaced format, where each image frame is composed of two image fields, each field holding same parity lines. However, many display devices require progressive video as input; also, many video processing tasks perform better on progressive material than on interlaced video. In the literature, there exist a great number of algorithms for interlaced to progressive video conversion, with a great tradeoff between the speed and quality of the results. The best algorithms in terms of image quality require motion compensation; hence, they are computationally very intensive. In this paper, we propose a novel deinterlacing algorithm based on ideas from the image inpainting arena. We view the lines to interpolate as gaps that we need to inpaint. Numerically, this is implemented using a dynamic programming procedure, which ensures a complexity of O(S), where S is the number of pixels in the image. The results obtained with our algorithm compare favorably, in terms of image quality, with state-of-the-art methods, but at a lower computational cost, since we do not need to perform motion field estimation.
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