Remote Sensing Image Matching Based Improved ORB in NSCT Domain

Dan Ma,Hui-cheng Lai

doi:10.1007/s12524-019-00958-y

Dan Ma, Hui-cheng Lai

Open Access

https://doi.org/10.1007/s12524-019-00958-y

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Abstract

Aiming at the problem that the ORB algorithm has no scale invariance and low matching accuracy in image matching, an improved ORB algorithm is proposed on the basis of SURF algorithm. Based on the flexibility of NSCT in image decomposition and the effectiveness of the improved ORB algorithm in remote sensing image matching, an improved ORB algorithm based on NSCT domain is proposed for remote sensing image matching. The image to be matched and the reference image are decomposed by NSCT. Two corresponding low-frequency images are obtained. Then, to reduce the influence of high-frequency noise on matching results, two low-frequency images are inputted to the improved ORB algorithm to obtain initial match results. The RANSAC algorithm is adopted to eliminate the mismatching points and complete the image matching. The experimental results show that the algorithm can make up the problem that the ORB algorithm has no scale invariance, and effectively improve the matching speed and accuracy of scale and rotation changes between two images. Meanwhile, the algorithm is more robust than classical methods in many complex situations such as image blur, field of view change, and noise interference.

Highlights

Image matching is the basic component of the field of machine vision, which is widely used in many fields, such as medicine, agriculture, remote sensing, machinery and artificial intelligence, etc. (Uchiyama et al 2015; Schmid et al 2000; Reese et al 2015; Sedaghat and Ebadi 2015; Lee et al 2016; Ye et al 2017)
Aiming at the problem that the Oriented Brief algorithm (ORB) algorithm has no scale invariance and low matching accuracy in image matching, an improved ORB algorithm is proposed on the basis of Speed up robust feature (SURF) algorithm
Based on the flexibility of nonsubsampled contourlet (NSCT) in image decomposition and the effectiveness of the improved ORB algorithm in remote sensing image matching, an improved ORB algorithm based on NSCT domain is proposed for remote sensing image matching

Summary

Introduction

Image matching is the basic component of the field of machine vision, which is widely used in many fields, such as medicine, agriculture, remote sensing, machinery and artificial intelligence, etc. (Uchiyama et al 2015; Schmid et al 2000; Reese et al 2015; Sedaghat and Ebadi 2015; Lee et al 2016; Ye et al 2017). The experimental results show that the algorithm can make up the problem that the ORB algorithm has no scale invariance, and effectively improve the matching speed and accuracy of scale and rotation changes between two images.

Results

Conclusion