Name
Abstract | ||
|---|---|---|
The advent of GPUs with programmable shaders on handheld devices has motivated embedded application developers to utilize GPU to offload computationally intensive tasks and relieve the burden from embedded CPU. In this work, we propose an image processing toolkit on handheld GPU with programmable shaders using OpenGL ES 2.0 API. By using the image processing toolkit, we show that a range of image processing algorithms map readily to handheld GPU. We employ real-time video scaling, cartoon-style non-photorealistic rendering, and Harris corner detector as our example applications. In addition, we propose techniques to achieve increased performance with optimized shader design and efficient sharing of GPU workload between vertex and fragment shaders. Performance is evaluated in terms of frames per second at varying video stream resolution. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICIP.2010.5651740 | Image Processing |
Keywords | Field | DocType |
application program interfaces,computer graphic equipment,coprocessors,notebook computers,optimisation,rendering (computer graphics),video streaming,API,GPU,Harris corner detector,OpenGL ES 2.0,cartoon style non photorealistic rendering,embedded CPU,handheld device,image processing,optimization,programmable shaders,real time video scaling,video stream resolution,GPGPU,GPU,OpenGL ES 2.0,mobile computing,mobile devices | Video post-processing,Computer graphics (images),Computer science,Image processing,General-purpose computing on graphics processing units,Digital image processing,Shader,Graphics processing unit,Computer hardware,Rendering (computer graphics),OpenGL | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4244-7993-1 | 978-1-4244-7993-1 | 19 |
PageRank | References | Authors |
1.08 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nitin Singhal | 1 | 113 | 10.55 |
| In Kyu Park | 2 | 316 | 35.97 |
| Sungdae Cho | 3 | 177 | 15.35 |