Shape From Focus by Total Variation

M. Mahmood
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引用次数: 10

Abstract

Usually, in Shape From Focus (SFF) methods, a single focus measure is applied on an image sequence to obtain an initial depth map and then an approximation technique is used to recover three-dimensional (3D) shape of an object. However, different focus measures perform differently in diverse conditions and it is hard to get accurate 3D shape based on a single focus measure. In this paper, we propose a nonlinear Total Variation (TV) based method for recovering 3D shape of an object by diffusing several initial depth maps obtained through different focus measures. Several experiments have been conducted using images of synthetic and real objects to evaluate the performance of the proposed method. Comparative analysis demonstrates of the effectiveness of the proposed approach.
形状从焦点的总变化
形状从焦点(Shape From Focus, SFF)方法通常是对图像序列进行单焦点测量获得初始深度图,然后使用近似技术恢复物体的三维形状。然而,不同的焦距测量在不同的条件下表现不同,基于单一的焦距测量很难获得准确的三维形状。本文提出了一种基于非线性全变分(TV)的方法,通过对不同焦点测量得到的多个初始深度图进行扩散来恢复物体的三维形状。利用合成物体和真实物体的图像进行了多次实验,以评估所提出方法的性能。对比分析表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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