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GPU implementation of JPEG XR

Ming C. Che, Jie Liang
Simon Fraser Univ., Canada
Visual Information Processing and Communication, Vol. 7543, No. 1. (2010), 754309.

@conference{che2010gpu,

   title={GPU implementation of JPEG XR},

   author={Che, M.C. and Liang, J.},

   booktitle={Proceedings of SPIE},

   volume={7543},

   pages={754309},

   year={2010}

}

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JPEG XR (formerly Microsoft Windows Media Photo and HD Photo) is the latest image coding standard. By integrating various advanced technologies such as integer hierarchical lapped transform, context adaptive Huffman coding, and high dynamic range coding, it achieves competitive performance to JPEG-2000, but with lower computational complexity and memory requirement. In this paper, the GPU implementation of the JPEG XR codec using NVIDIA CUDA (Compute Unified Device Architecture) technology is investigated. Design considerations to speed up the algorithm are discussed, by taking full advantage of the properties of the CUDA framework and JPEG XR. Experimental results are presented to demonstrate the performance of the GPU implementation.
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