School of Mechatronic Engineering and Automation, Shanghai University, No. 99 Shangda Road BaoShan District, Shanghai 200444, China.
Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada.
Sensors (Basel). 2019 Mar 22;19(6):1409. doi: 10.3390/s19061409.
Multi-focus image fusion is a technique for obtaining an all-in-focus image in which all objects are in focus to extend the limited depth of field (DoF) of an imaging system. Different from traditional RGB-based methods, this paper presents a new multi-focus image fusion method assisted by depth sensing. In this work, a depth sensor is used together with a colour camera to capture images of a scene. A graph-based segmentation algorithm is used to segment the depth map from the depth sensor, and the segmented regions are used to guide a focus algorithm to locate in-focus image blocks from among multi-focus source images to construct the reference all-in-focus image. Five test scenes and six evaluation metrics were used to compare the proposed method and representative state-of-the-art algorithms. Experimental results quantitatively demonstrate that this method outperforms existing methods in both speed and quality (in terms of comprehensive fusion metrics). The generated images can potentially be used as reference all-in-focus images.
多聚焦图像融合是一种获取所有物体都清晰聚焦的全聚焦图像的技术，旨在扩展成像系统的有限景深（DoF）。与传统基于 RGB 的方法不同，本文提出了一种新的多聚焦图像融合方法，该方法借助深度感应来辅助。在这项工作中，使用深度传感器和彩色相机来捕获场景的图像。使用基于图的分割算法从深度传感器中分割出深度图，并且使用分割区域来指导聚焦算法从多聚焦源图像中定位清晰的图像块，以构建参考全聚焦图像。使用五个测试场景和六个评估指标来比较所提出的方法和有代表性的最先进算法。实验结果定量证明，该方法在速度和质量（根据综合融合指标）方面均优于现有方法。生成的图像可以潜在地用作参考全聚焦图像。
