GPU-based edge-directed image interpolation

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Abstract

The rendering of lower resolution image data on higher resolution displays has become a very common task, in particular because of the increasing popularity of webcams, camera phones, and low-bandwidth video streaming. Thus, there is a strong demand for real-time, high-quality image magnification. In this work, we suggest to exploit the high performance of programmable graphics processing units (GPUs) for an adaptive image magnification method. To this end, we propose a GPU-friendly algorithm for image up-sampling by edge-directed image interpolation, which avoids ringing artifacts, excessive blurring, and staircasing of oblique edges. At the same time it features gray-scale invariance, is applicable to color images, and allows for real-time processing of full-screen images on today's GPUs. © Springer-Verlag Berlin Heidelberg 2007.

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Kraus, M., Eissele, M., & Strengert, M. (2007). GPU-based edge-directed image interpolation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4522 LNCS, pp. 532–541). Springer Verlag. https://doi.org/10.1007/978-3-540-73040-8_54

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