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

Background

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.