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GP-grid image interpolation and denoising for division of focal plane sensors

机译:焦平面传感器分割的GP网格图像插值和去噪

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Image interpolation and denoising are important techniques in image processing. Recently, there has been a growing interest in the use of Gaussian processes (GP) regression for interpolation and denoising of image data. However, exact GP regression suffers from O (N~3) runtime for data size N, making it intractable for image data. Our GP-grid algorithm reduces the runtime complexity of GP from O (N~3) to O (N~(3/2)). We provide comprehensive mathematical model as well as experimental results of the GP interpolation performance for division of focal plane polarimeter. The GP interpolation method outperforms the commonly used bilinear interpolation method for polarimeters.
机译:图像插值和去噪是图像处理中的重要技术。最近,人们对使用高斯过程(GP)回归进行图像数据的内插和去噪越来越感兴趣。但是,对于数据大小N,精确的GP回归会受到O(N〜3)运行时间的影响,这对于图像数据来说是棘手的。我们的GP网格算法将GP的运行时复杂度从O(N〜3)降低到O(N〜(3/2))。我们为焦平面旋光仪的划分提供了综合的数学模型以及GP插值性能的实验结果。 GP插值方法优于旋光仪常用的双线性插值方法。

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