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Image-processing methods on general-purpose graphics processors with parallel architecture

机译:具有并行体系结构的通用图形处理器上的图像处理方法

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This paper discusses the principles of massively parallel computations for digital signal processing by means of NVIDIA CUDA technology, using as examples such operations as the inversion of image brightnesses, gamma correction, and the Sobel operator. The main methods of digital image processing using massive parallelism of the computations on a graphics processing unit are evaluated. These methods are implemented on the central processing unit and the graphics processing unit and are compared in terms of such parameters as the time to carry out the processing, the size of the images that are used, and the size of the memory blocks used by the CUDA architecture.
机译:本文以NVIDIA CUDA技术为例,讨论了数字信号处理中大规模并行计算的原理,并以图像亮度反转,伽马校正和Sobel运算符等操作为例。评估了在图形处理单元上使用大量并行计算的数字图像处理的主要方法。这些方法在中央处理单元和图形处理单元上实现,并根据以下参数进行比较:执行处理的时间,所使用图像的大小以及内存使用的存储块的大小。 CUDA体系结构。

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