Research on aerial image mosaic algorithm based on SIFT features of superpixels

WANG Ping; WANG Gang

doi:10.13873/J.1000-9787(2016)12-0017-03

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Research on aerial image mosaic algorithm based on SIFT features of superpixels

更新时间：2025-09-11

- Research on aerial image mosaic algorithm based on SIFT features of superpixels
- Vol. 35, Issue 12, Pages: 17-19+23(2016)
- 作者机构：
  
  天津大学电气与自动化工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2016)12-0017-03
  CLC： TP391.41
- Published：2016
- 稿件说明：
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[1]王萍,王港.超像素SIFT特征航拍地图拼接研究[J].传感器与微系统,2016,35(12):17-19+23.

WANG Ping, WANG Gang. Research on aerial image mosaic algorithm based on SIFT features of superpixels[J]. 2016, 35(12): 17-19+23.
[1]王萍,王港.超像素SIFT特征航拍地图拼接研究[J].传感器与微系统,2016,35(12):17-19+23. DOI： 10.13873/J.1000-9787(2016)12-0017-03.

WANG Ping, WANG Gang. Research on aerial image mosaic algorithm based on SIFT features of superpixels[J]. 2016, 35(12): 17-19+23. DOI： 10.13873/J.1000-9787(2016)12-0017-03.

摘要

为解决航拍地图拼接计算量大、内容复杂多变的问题

提出使用超像素尺度不变特征变换（SIFT）特征进行地图拼接。首先利用近邻传播（AP）算法改进简单线性迭代聚类（SLIC）算法实现超像素自适应分割。然后在引导信息下对少数超像素提取SIFT特征

进行SIFT特征匹配。最后在线生成监督机制

在随机抽样一致性（RANSAC）算法配合下

得到少而精的匹配点

计算变换矩阵融合图像

实现图像拼接。实验结果显示:对于较高分辨率的图像

该算法与单纯SIFT拼接算法相比

在计算时间和拼接质量上都显示出较大的优势。

Abstract

In order to address dynamically changing contents and large computation in aerial image mosaic

propose a region-matching algorithm based on scale invariant feature transform（ SIFT） features of superpixels.Firstly

improve a simple linear iterative clustering（ SLIC） by affinity propagation（ AP）

and the method is used to accomplish adaptive superpixel segmentation; Next

a few superpixels are described with SIFT features to acquire coarse point matching under the guidance. Finally

supervision is obtained online to select more superpixels to be matched and random sample consensus（ RANSAC） method is constructed so that aerial image mosaic is accomplished precisely. Experimental results demonstrate that

compared with SIFT mosaic algorithm in high resolution

the method greatly reduces computation time and improves quality of aerial image mosaic.

关键词

Keywords

references

基于改进的Harris和SIFT算法的眼底图像拼合 [J]. 陶治江,黄华. 计算机工程与设计 . 2012(09)

Automatic Panoramic Image Stitching using Invariant Features [J] . Matthew Brown,David G. Lowe. International Journal of Computer Vision . 2007 (1)

Distinctive Image Features from Scale-Invariant Keypoints [J] . David G. Lowe. International Journal of Computer Vision . 2004 (2)

Random sample consensus [J] . Martin A. Fischler,Robert C. Bolles. Communications of the ACM . 1981 (6)

Multidimensional binary search trees used for associative searching [J] . Jon Louis Bentley. Communications of the ACM . 1975 (9)

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