基于光流跟踪和 Delaunay 三角测量的多焦点图像配准

IF 3.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Xiaohua Xia , Dianbin Yang , Shaobo Huo , Jianhong Sun , Huatao Xiang
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引用次数: 0

摘要

在多焦点图像融合和从焦点看形状领域,精确的多焦点图像配准是一个关键的先决条件。由于失焦区域的特征检测困难以及全局配准方法的局限性,传统的多焦图像配准方法精度较低。为解决这一问题,本文提出了一种基于光流跟踪和 Delaunay 三角测量的新型多焦点图像配准方法。这一创新包括两个方面。首先,利用光流跟踪提取和匹配多焦点图像的非倾斜特征。这大大增加了多焦点图像散焦区域的匹配特征数量。二是采用 Delaunay 三角测量法进行局部配准。它使匹配特征严格对齐。实验结果表明,所提出的方法在图像配准精度和图像融合质量方面均优于传统方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-focus image registration based on optical flow tracking and Delaunay triangulation
In the fields of multi-focus image fusion and shape from focus, accurate registration of multi-focus images is a crucial prerequisite. Due to the difficulty of feature detection in defocused regions and the limitations of global registration methods, traditional multi-focus image registration methods have low accuracy. To solve this problem, a novel multi-focus image registration method based on optical flow tracking and Delaunay triangulation is proposed. The innovation includes two aspects. The first is that optical flow tracking is utilized to extract and match the non-salient features of multi-focus images. It greatly increases the number of matching features in the defocused regions of multi-focus images. The second is that Delaunay triangulation is adopted for local registration. It makes the matching features strictly aligned. The results of the experiments show that the proposed method is superior to the traditional methods in terms of image registration accuracy and image fusion quality.
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来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
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