吉林大学学报（信息科学版）2017，Vol.35Issue(2)：188-197,10.
基于SIFT算法的无人机遥感图像拼接技术
Matching Technologies of UAV Remote Sensing Image Based on SIFT
摘要
Abstract
In order to provide a panoramic image with high precision and wide field,the main purpose of this study is to achieve a high-resolution images stitching.For a large number of high-resolution farmland remote sensing images taken by UAV (Unmanned Aerial Vehicle),to obtain the full panoramic farmland image,the image mosaic algorithm is improved by combining with characteristics of UAV image.In detecting the candidate points step preliminarily using SIFT (Scale-Invariant Feature Transform) algorithm,we use adaptive threshold to remove part of the candidate feature points.By combining with latitude,longitude coordinates and the relative position relation of the overlapping area about UAV image,we remove part of invalid feature points and make rough matching on feature point.For completing two adjacent farmland remote sensing images stitching,we apply random sample consensus algorithm to eliminate mismatching point,and solve the projective transformation matrix.In order to complete 128 high-resolution images stitching,we design pyramid stitching strategy.The experimental results show that:with the improved feature points streamline method on SIFT algorithm,the time needed for the rough feature points matching is reduced by an average of 52％,and 25％ reduction for Accurate feature points matching.In comparison experiment based on six evaluation parameters,we found that the multi-resolution image fusion algorithm is superior to other fusion algorithms in qualitative and quantitative analysis.The study provides an efficient reference for a large number of high-resolution image stitching.关键词
农田遥感图像拼接/SIFT算法/特征点匹配/无人机/图像融合Key words
farmland remote sensing image stitching/SIFT algorithm/feature point matching/unmanned aerial vehide (UAV)/image fusion分类
信息技术与安全科学引用本文复制引用
王茜,宁纪锋,曹宇翔,韩文霆..基于SIFT算法的无人机遥感图像拼接技术[J].吉林大学学报（信息科学版）,2017,35(2):188-197,10.基金项目
国家自然科学基金青年基金资助项目(31501228) （31501228）
科技部国际合作基金资助项目(2014DFG72150) （2014DFG72150）
杨凌示范区工业基金资助项目(2015GY-03) （2015GY-03）
陕西省自然科学基金资助项目(2015JM3110) （2015JM3110）
国家级大学生创新创业训练计划基金资助项目(201610712064) （201610712064）
