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首页> 外文期刊>International journal of quantum information >Bilinear interpolation method for quantum images based on quantum Fourier transform
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Bilinear interpolation method for quantum images based on quantum Fourier transform

机译:基于量子傅里叶变换的量子图像的双线性插值方法

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摘要

Image scaling is the basic operation that is widely used in classic image processing, including nearest-neighbor interpolation, bilinear interpolation, and bicubic interpolation. In quantum image processing (QIP), the research on image scaling is focused on nearest-neighbor interpolation, while the related research of bilinear interpolation is very rare, and that of bicubic interpolation has not been reported yet. In this study, a new method based on quantum Fourier transform (QFT) is designed for bilinear interpolation of images. Firstly, some basic functional modules are constructed, in which the new method based on QFT is adopted for the design of two core modules (i.e. addition and multiplication), and then these modules are used to design quantum circuits for the bilinear interpolation of images, including scaling-up and down. Finally, the complexity analysis of the scaling circuits based on the elementary gates is deduced. Simulation results show that the scaling image using bilinear interpolation is clearer than that using the nearest-neighbor interpolation.
机译:图像缩放是广泛应用于经典图像处理的基本操作,包括最近邻的插值,双线性插值和双向插值。在量子图像处理(QIP)中,图像缩放的研究集中在最近邻的插值上,而Bilinear插值的相关研究非常罕见,并且尚未报告双层插值。在该研究中,设计了一种基于量子傅里叶变换(QFT)的新方法,用于自动插值的图像。首先,构造了一些基本功能模块,其中采用了基于QFT的新方法,用于设计两个核心模块(即加法和乘法),然后这些模块用于设计图像的双线性插值的量子电路,包括缩放和下降。最后,推导了基于基于基部门的缩放电路的复杂性分析。仿真结果表明,使用Bilinear插值的缩放图像比使用最近邻插值更清晰。

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