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Implementation and optimization of image processing algorithms on handheld GPU

Nitin Singhal, In Kyu Park, Sungdae Cho
Digital Media & Communication R&D Center, SAMSUNG Electronics Co. Ltd., Suwon, South Korea
17th IEEE International Conference on Image Processing (ICIP), 2010

@conference{singhal2010implementation,

   title={Implementation and optimization of image processing algorithms on handheld GPU},

   author={Singhal, N. and Park, I.K. and Cho, S.},

   booktitle={Image Processing (ICIP), 2010 17th IEEE International Conference on},

   pages={4481–4484},

   issn={1522-4880},

   organization={IEEE}

}

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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.
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