吉林大学学报(信息科学版) ›› 2024, Vol. 42 ›› Issue (5): 901-907.

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基于SIFT 特征点提取算法的三维数字影像重建方法

李  静   

  1. 文华学院城市建设工程学部,武汉430074
  • 收稿日期:2023-06-01 出版日期:2024-10-21 发布日期:2024-10-23
  • 作者简介:李静(1987— ), 女, 石家庄人, 文华学院副教授, 主要从事新媒体艺术研究, (Tel)86-15926392450(E-mail) lijing19870530@ 163. com。
  • 基金资助:
    湖北省教育厅科学研究计划基金资助项目(B2017403)

Research on Method of Engine Fault Diagnosis Based on Improved Minimum Entropy Deconvolution 

 LI Jing   

  1. Department of City Construction, Wenhua College, Wuhan 430074, China
  • Received:2023-06-01 Online:2024-10-21 Published:2024-10-23

摘要:  针对在数字影像三维重建过程中,由于原始数据中存在噪声和失真等不足,导致特征匹配效率和精度 较低的问题,提出基于SIFT(Scale-Invariant Feature Transform)特征点提取算法的三维数字影像重建方法。 采用双边滤波算法对数字影像中的环境噪声实施消除处理,并保留数字影像的边缘信息,提高特征点提取 精度; 通过尺度不变特征转换(SIFT)算法对其提取特征点, 得到数字影像的特征点对; 将该特征点对作为 初始面片,利用空间目标多视影像密集匹配方法, 实现对数字影像的三维重建。 实验结果表明,所提方法 特征匹配效率和匹配精度高,且降噪能力强,生成的三维重建影像所需平均时间为26.74 ms

关键词: SIFT算法, 双边滤波, 去噪;特征匹配;三维重建

Abstract: In the process of 3D reconstruction of digital images, problems such as noise and distortion in the original data lead to low efficiency and accuracy of feature matching. To address this issue, a 3D digital image reconstruction method based on SIFT(Scale-Invariant Feature Transform) feature point extraction algorithm is proposed. The Bilateral filter algorithm is used to eliminate the environmental noise in the digital image, retain the edge information of the digital image, and improve the accuracy of feature point extraction. The SIFT algorithm is used to obtain feature point pairs. Using this feature point pair as the initial patch, a dense matching method for spatial object multi view images is used to achieve 3D reconstruction of digital images. The experimental results show that the proposed method has high feature matching efficiency and accuracy and strong noise reduction ability. The average time required for generating 3D reconstructed images is 26. 74 ms. 

Key words: scale invariant feature transform(SIFT) algorithm, bilateral filter, denoising, feature matching, three-dimensional reconstruction

中图分类号: 

  • TP391