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Image deblurring using projective geometry and natural image statistics

机译:使用投影几何和自然图像统计进行图像去模糊

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The camera motion during image capturing results in poor and spoiled images. The conventional available methods to remove the camera shake assumes uniform spatial blur on the image, which in most of the cases is not a true assumption. Most of the available methods model the blur image as a convolution of sharp image and a blurring kernel, these results in more number of unknown parameters than known parameters. We propose a projective geometry non-uniform image deblurring model to handle the spatial non-uniformity in the blurred image. We also consider the results of research done in natural image statistics in our prior assumptions of blurring kernel and sharp image to increase the number of known parameters. We present a fully automated GUI based algorithm to make the application user friendly.
机译:图像拍摄期间相机的运动会导致图像质量差和变质。消除相机抖动的常规可用方法假定图像上出现均匀的空间模糊,这在大多数情况下不是真实的假设。大多数可用的方法将模糊图像建模为清晰图像和模糊内核的卷积,与已知参数相比,这些方法导致未知参数的数量更多。我们提出了一种投影几何非均匀图像去模糊模型,以处理模糊图像中的空间非均匀性。我们还考虑了在先前对内核和清晰图像进行模糊处理以增加已知参数的数量的前提下,在自然图像统计中进行的研究结果。我们提出了一种基于GUI的全自动算法,以使应用程序易于使用。

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