王平, 全吉成, 赵柏宇. 基于双线性插值的图像缩放在GPU上的实现[J]. 微电子学与计算机, 2016, 33(11): 129-132.
引用本文: 王平, 全吉成, 赵柏宇. 基于双线性插值的图像缩放在GPU上的实现[J]. 微电子学与计算机, 2016, 33(11): 129-132.
WANG Ping, QUAN Ji-cheng, ZHAO Bo-yu. Realization of Image Zooming in GPU Based on Bilinear Interpolation[J]. Microelectronics & Computer, 2016, 33(11): 129-132.
Citation: WANG Ping, QUAN Ji-cheng, ZHAO Bo-yu. Realization of Image Zooming in GPU Based on Bilinear Interpolation[J]. Microelectronics & Computer, 2016, 33(11): 129-132.

基于双线性插值的图像缩放在GPU上的实现

Realization of Image Zooming in GPU Based on Bilinear Interpolation

  • 摘要: 针对传统的在CPU上实现的基于双线性插值的图像缩放存在速度慢等问题, 利用GPU高性能并行计算优势, 实现了在GPU上基于双线性插值的快速缩放.此算法将目标图像的每个像素分配给GPU中每个线程同时执行, 提高插值效率.从实验结果可以看出, 此算法在放大图像时, 随着图像分辨率的增大, GPU的插值速度相对CPU单线程和多线程的插值速度显著提高, 能很好达到实时缩放图像的效果.

     

    Abstract: The traditional image scaling algorithm in CPU based on bilinear interpolation has to confront with the problem of slow scaling. In this paper, GPU as a burgeoning high performance computing technique, implemented fast zooming on the GPU based on bilinear interpolation. In this algorithm, each pixel of the target image is allocated to each thread in GPU, and the interpolation efficiency is improved. The experimental results show that compared with the CPU single thread and multi thread, this algorithm significantly improved the interpolation speed of GPU, with the increase of the image resolution, and can achieve the effect of real-time image zooming.

     

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