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Bayesian image super resolution

机译:贝叶斯图像超分辨率

摘要

An image super resolution system computes a high resolution image of a target from multiple low resolution images of the same target. Each low resolution image differs slightly in perspective from each of the other low resolution images. A coarse registration operation determines initial estimates of registration parameters (e.g., representing shifts and rotation in perspective) associated with each low resolution image. A fine registration operation improves the initial estimates using Bayesian analysis to infer the registration parameters and an acuity parameter. As such, a marginal likelihood of the low resolution images is optimized to determine the improved estimates of the registration parameters and the acuity parameter, which are used to solve for the high resolution image.
机译:图像超分辨率系统从同一目标的多个低分辨率图像中计算目标的高分辨率图像。每个低分辨率图像的透视图与其他每个低分辨率图像的透视图都略有不同。粗略的配准操作确定与每个低分辨率图像相关联的配准参数的初始估计(例如,表示透视中的移位和旋转)。精细配准操作使用贝叶斯分析改进初始估计,以推断配准参数和敏锐度参数。这样,低分辨率图像的边际可能性被优化以确定对配准参数和敏锐度参数的改进估计,其用于解决高分辨率图像。

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