Remote sensing image mosaic technology based on SURF algorithm in agriculture

Weiping Zhang,Xiujuan Li,Junfeng Yu,Mohit Kumar,Yihua Mao

doi:10.1186/s13640-018-0323-5

Weiping Zhang, Xiujuan Li + Show 3 more

Open Access

https://doi.org/10.1186/s13640-018-0323-5

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Abstract

The remote sensing technology of unmanned aerial vehicle (UAV) is a low altitude remote sensing technology. The technology has been widely used in military, agricultural, medical, geographical mapping, and other fields by virtue of the advantages of fast acquisition, high resolution, low cost, and good security. But limited by the flying height of UAV and the focal length of the digital camera, the single image obtained by the UAV is difficult to form the overall cognition of the ground farmland area. In order to further expand the field of view, it is necessary to mosaic multiple single images acquired by UAV into a complete panoramic image of the farmland. In this paper, aiming at the problem of UAV low-altitude remote sensing image splicing, an image mosaic technique based on Speed Up Robust Feature (SURF) is introduced to achieve rapid image splicing. One hundred fifty ground farmland remote sensing images collected by UAV are used as experimental splicing objects, and the image splicing is completed by the global stitching strategy optimized by Levenberg-Marquardt (L-M). Experiments show that the strategy can effectively reduce the influence of cumulative errors and achieve automatic panoramic mosaic of the survey area.

Highlights

At present, remote sensing images have become an important means of information acquisition
In order to solve the interference of translation, rotation and scale change between the images to be stitched, the Scale invariant feature transform (SIFT) algorithm realizes the matching of the features of two different images by extracting the invariant feature points of the image, and forms a high quality panoramic image by matching a number of same name points to the unmanned aerial vehicle (UAV) remote sensing image [10]
The UAV equipped with a Charge-coupled device (CCD) digital camera can acquire surface images flexibly, and the image accuracy is high

Summary

Introduction

Remote sensing images have become an important means of information acquisition. In order to solve the interference of translation, rotation and scale change between the images to be stitched, the SIFT algorithm realizes the matching of the features of two different images by extracting the invariant feature points of the image, and forms a high quality panoramic image by matching a number of same name points to the UAV remote sensing image [10] This algorithm has a large amount of computation, and it is impossible to accurately identify and extract feature points from images with less blurred edges or feature points, and it is not possible to clearly identify edges and outlines. The instability of the photographic posture results in the continuous splicing of cumulative errors, and in severe cases, the distortion of the local edges In view of these characteristics, this paper adopts the image mosaic based on SURF features, and uses the UAV remote sensing image data to verify the algorithm. The SURF algorithm has greatly improved the speed and stability of feature points

Method-image feature extraction and mosaic algorithm

The transformation parameter estimation

Experimental results and discussions

Conclusions