IoT 18(16): e2

Research Article

Image Registration Model For Remote Sensing Images

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  • @ARTICLE{10.4108/eai.21-12-2018.159333,
        author={Sabeen Gul and Sheeraz Memon and Bushra Naz},
        title={Image Registration Model For Remote Sensing Images},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={4},
        number={16},
        publisher={EAI},
        journal_a={IOT},
        year={2018},
        month={10},
        keywords={Image registration, SIFT, KNN, RANSAC, High Resolution Images},
        doi={10.4108/eai.21-12-2018.159333}
    }
    
  • Sabeen Gul
    Sheeraz Memon
    Bushra Naz
    Year: 2018
    Image Registration Model For Remote Sensing Images
    IOT
    EAI
    DOI: 10.4108/eai.21-12-2018.159333
Sabeen Gul1,*, Sheeraz Memon1, Bushra Naz1
  • 1: Department of Computer System Engineering Mehran University of Engineering and Technology Jamshoro
*Contact email: Sabeenmemon22@gmail.com

Abstract

Image registration is the vital technology in computer vision. By developing precise image registration algorithm will meaningfully improve the techniques for the problems in computer vision. Registration process does geometrical alteration that aligns point present in one view of an object with similar points in another view of that object or another object .Steps involved in image registration are feature finding, matching of features, image transformation and resampling. Feature finding and matching have vital role in accuracy of the process. In this paper we have used SIFT (Scale Invariant Feature Transform) for the feature detection which is invariant to scaling, rotation and noise. KNN nearest neighbor is used for matching similar points and the other efficient method in reducing miss matches in the proposed algorithm is Random sample consensus method.