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GPU-based JPEG2000 decoding scheme for digital cinema

机译:用于数字电影的基于GPU的JPEG2000解码方案

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For the digital cinema system specification released by Digital Cinema Initiatives, it was decided to use 2K or 4K images encoded by the JPEG2000 standard. JPEG2000 provides high compression rates and error tolerance, but it is a burden for both encoding and decoding. To improve the decoding performance, a parallel computing architecture called CUDA has been receiving a lot of attention recently. In this paper, we attempt to realize a real-time JPEG2000 decoding scheme for digital cinema using multiple CPU cores and GPUs. We present CUDA algorithms that perform inverse quantization, inverse 2D discrete wavelet transform and inverse irreversible color transform on a CUDA device, which brings us significant performance gain on a general CPU without extra cost.
机译:对于Digital Cinema Initiatives发布的数字电影系统规范,决定使用由JPEG2000标准编码的2K或4K图像。 JPEG2000提供了很高的压缩率和容错能力,但这对编码和解码都是沉重的负担。为了提高解码性能,近来称为CUDA的并行计算架构受到了很多关注。在本文中,我们尝试使用多个CPU内核和GPU实现用于数字电影的实时JPEG2000解码方案。我们介绍了CUDA算法,该算法在CUDA设备上执行逆量化,逆2D离散小波逆变换和逆不可逆颜色变换,这使我们在普通CPU上获得了显着的性能提升,而没有额外的成本。

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