This article describes an image processing algorithm to identify the size and shape of a spherical reflecting celestial body prominently depicted in images taken from a spacecraft with an optical camera, with the purpose of estimating the relative distance between target and observer in magnitude and direction. The approach is based on the fact that in such images, the pixels belonging to the target’s hard edge have the highest values of the image derivative; therefore, they are easily recognizable when the image is processed with a gradient filter. Eventual extraneous points polluting the dataset (outliers) are eliminated by two methods applied in sequence. The target center and radius are estimated by non-linear least squares using circular sigmoid functions. The proposed image processing has been applied to real and synthetic Moon images. An error analysis is also performed to determine the performance of the proposed method.
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