首页> 外文会议>Conference on Human Vision and Electronic Imaging IX; 20040119-20040121; San Jose,CA; US >Implementation of a visual difference metric using commodity graphics hardware
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Implementation of a visual difference metric using commodity graphics hardware

机译:使用商品图形硬件实现视觉差异度量

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A visual difference metric was implemented on a commodity graphics card to take advantage of the increased processing power available today in a Graphics Processing Unit (GPU). The specific algorithm employed was the Sarnoff Visual Discrimination Metric (Sarnoff VDM). To begin the implementation, the typical architecture of a contemporary GPU was analyzed and some general strategies were developed for performing image processing tasks on GPUs. The stages of the Sarnoff VDM were then mapped onto the hardware and the implementation was completed. A performance analysis showed that the algorithm's speed had been increased by an order of magnitude over the original version that only ran on a CPU. The same analysis showed that the energy stage was the most expensive in terms of both program size and processing time. An interactive version of the Sarnoff VDM was developed and some ideas for additional applications of GPU based visual difference metrics were suggested.
机译:在商品图形卡上实现了视觉差异度量,以利用当今图形处理单元(GPU)中可用的增强处理能力。所采用的特定算法是Sarnoff视觉区分指标(Sarnoff VDM)。为了开始实施,分析了当代GPU的典型架构,并开发了一些用于在GPU上执行图像处理任务的通用策略。然后将Sarnoff VDM的阶段映射到硬件上,并完成了实现。性能分析表明,该算法的速度比仅在CPU上运行的原始版本提高了一个数量级。相同的分析表明,就程序大小和处理时间而言,能量级是最昂贵的。开发了Sarnoff VDM的交互式版本,并针对基于GPU的视觉差异度量的其他应用提出了一些想法。

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