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GPU Implementation of JPEG XR

机译:GPU实现JPEG XR

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摘要

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.
机译:JPEG XR(以前的Microsoft Windows Media Photo照片和HD Photo)是最新的图像编码标准。通过整合各种先进技术,如整数分层覆盖的变换,上下文自适应霍夫曼编码和高动态范围编码,它可以实现对JPEG-2000的竞争性能,但具有较低的计算复杂性和内存要求。本文研究了使用NVIDIA CUDA(计算统一设备架构)技术的JPEG XR编解码器的GPU实现。通过充分利用CUDA框架和JPEG XR的属性,讨论了加速算法的设计注意事项。提出了实验结果来证明GPU实施的表现。

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