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Improved estimation of defocus blur and spatial shifts in spatial domain: a homotopy-based approach

机译:改进的散焦模糊和空间域中空间移位的估计:基于同伦的方法

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This paper presents a homotopy-based algorithm for the recovery of depth cues in the spatial domain. The algorithm specifically deals with defocus blur and spatial shifts, that is 2D motion, stereo disparities and/or zooming disparities. These cues are estimated from two images of the same scene acquired by a camera evolving in time and/or space. We show that they can be simultaneously computed by resolving a system of equations using a homotopy method. The proposed algorithm is tested using synthetic and real images. The results confirm that the use of a homotopy method leads to a dense and accurate estimation of depth cues. This approach has been integrated into an application for relief estimation from remotely sensed images. (C) 2003 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved. [References: 33]
机译:本文提出了一种基于同伦算法的空间域深度线索的恢复。该算法专门处理散焦模糊和空间偏移,即2D运动,立体视差和/或缩放视差。这些提示是从同一场景的两个图像中估计的,这些图像是由在时间和/或空间上演变的相机获取的。我们表明,可以通过使用同伦方法解析方程组来同时计算它们。使用合成图像和真实图像对提出的算法进行了测试。结果证实,使用同伦方法可以对深度线索进行密集而准确的估计。该方法已集成到用于从遥感图像进行地貌估计的应用程序中。 (C)2003模式识别学会。由Elsevier Science Ltd.出版。保留所有权利。 [参考:33]

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