恢复在分辨率极限下获得的运动物体的模糊摄影图像

Victor B. Fedorov, Sergey G. Kharlamov, Anatoly I. Starikovskiy
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引用次数: 0

摘要

目标。在处理卫星获得的地球表面图像时,如何恢复运动物体的模糊图像具有重要的实际意义。本工作的目的是研究在相机分辨率极限下提高模糊图像恢复质量的可能性。采用了基于错误和病态问题理论的数字信号处理方法。所提出的恢复运动物体的模糊图像的方法与传统方法的不同之处在于,恢复模糊图像问题的离散卷积方程是通过基于Kotelnikov插值级数逼近相应的积分方程而得到的,而不是基于传统的正交公式。在工作中,得到了计算用Kotelnikov插值级数得到的卷积核的公式。离散卷积反演问题属于不适定问题,需要正则化。比较了传统的基于Tikhonov正则化的正交公式和基于Kotelnikov插值序列的方法对模糊图像的恢复效果。虽然在两种情况下,模糊图像恢复的质量几乎是相同的,但在正交公式中,模糊值表示为整数像素,而当使用Kotelnikov级数时,该值也可以指定为像素的分数。本文论证了在处理相机极限分辨率下获得的模糊图像时,基于Kotelnikov插值级数离散化描述模糊型图像畸变的卷积的方便性。在这种情况下,模糊的数量可以表示为一个像素的分数。这种情况通常出现在处理地球表面的卫星照片时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Restoration of a blurred photographic image of a moving object obtained at the resolution limit
Objectives. When processing images of the Earth’s surface obtained from satellites, the problem of restoring a blurry image of a moving object is of great practical importance. The aim of this work is to study the possibility of improving the quality of restoration of blurry images obtained at the limit of the resolution of the camera.Methods. Digital signal processing methods informed by the theory of incorrect and ill-conditioned problems were used.Results. The proposed method for restoring a blurred photographic image of a moving object differs from traditional approaches in that the discrete convolution equation, to which the problem of restoring a blurred image is reduced, is obtained by approximating the corresponding integral equation based on the Kotelnikov interpolation series rather than on the traditional basis of the quadrature formula. In the work, formulas are obtained for calculating the kernel of the convolution obtained using the Kotelnikov interpolation series. The discrete convolution inversion problem, which belongs to the class of ill-posed problems, requires regularization. Results of traditional approaches to restoring blurred images using the quadrature formula with Tikhonov regularization and the proposed method based on the Kotelnikov interpolation series are compared. Although the quality of the blurred image restoration is almost the same in both cases, in the quadrature formula the blur value is expressed as an integer number of pixels, while, when using the Kotelnikov series, this value can also be specified in fractions of a pixel.Conclusions. The expediency of discretizing the convolution describing the image distortion of the blur type on the basis of the Kotelnikov interpolation series when processing a blurred image obtained at the limit of the resolution of the camera is demonstrated. In this case, the amount of blur can be expressed in fractions of a pixel. This situation typically arises when processing satellite photography of the Earth’s surface.
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