GPU-Based Edge-Directed Image Interpolation
Martin Kraus*, Mike Eissele, Magnus Strengert
*Computer Graphics and Visualization Group, Technische Universität München, Germany
Visualization and Interactive Systems Group, Universität Stuttgart, Germany
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, highquality 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 GPUfriendly 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.