A computational approach to edge detection
Readings in computer vision: issues, problems, principles, and paradigms
Semi-automatic generation of transfer functions for direct volume rendering
VVS '98 Proceedings of the 1998 IEEE symposium on Volume visualization
Image analysis with local binary patterns
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
New edge-directed interpolation
IEEE Transactions on Image Processing
Image up-sampling using total-variation regularization with a new observation model
IEEE Transactions on Image Processing
ACM SIGGRAPH 2008 posters
Sub-pixel data fusion and edge-enhanced distance refinement for 2D/3D images
International Journal of Intelligent Systems Technologies and Applications
Sub-pixel data fusion and edge-enhanced distance refinement for 2D/3D images
International Journal of Intelligent Systems Technologies and Applications
CPU, SMP and GPU implementations of Nohalo level 1, a fast co-convex antialiasing image resampler
C3S2E '09 Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering
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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.