Enhancement of Depth Map through Weighted Combination of Guided Image Filters in Shape-From-Focus

Zubair Ahmed, Ahsan Shahzad, Usman Ali
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引用次数: 2

Abstract

Estimation of depth map plays a key role in a number of computer vision applications. Shape from focus is a monocular approach that uses image focus as a cue to reconstruct 3D shapes. In the literature, a variety of guided image filters have been proposed to enhance the depth map individually. Among them, some have excess computational time burden, and some others produce unsatisfactory results. This paper proposed a framework for the enhancement of depth map by using a weighted combination of selected guided filters in shape from focus. The optimized weights are obtained using the particle swarm optimization approach, and the subset of best-performing filters is identified through a sequential forward search method. The experimental results have demonstrated that the proposed framework provides considerably improved depth maps.
聚焦形状引导图像滤波器加权组合增强深度图
深度图估计在许多计算机视觉应用中起着关键作用。形状从焦点是一种单眼方法,使用图像焦点作为线索重建三维形状。在文献中,已经提出了各种引导图像滤波器来单独增强深度图。其中,有的计算时间负担过重,有的计算结果不理想。本文提出了一种深度图增强的框架,该框架利用从焦点中选择的形状引导滤波器的加权组合增强深度图。采用粒子群优化方法获得最优权重,并通过序贯前向搜索方法确定最优滤波器子集。实验结果表明,提出的框架提供了显著改进的深度图。
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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