Image Registration Model For Remote Sensing Images
| Autor: | Sheeraz Memon, Bushra Naz, Sabeen Gul |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Matching (statistics)
lcsh:Computer engineering. Computer hardware lcsh:T55.4-60.8 Computer science KNN 0211 other engineering and technologies ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-invariant feature transform Image registration lcsh:TK7885-7895 02 engineering and technology High Resolution Images k-nearest neighbors algorithm SIFT 0202 electrical engineering electronic engineering information engineering lcsh:Industrial engineering. Management engineering Computer vision 021101 geological & geomatics engineering Feature detection (computer vision) RANSAC business.industry Feature (computer vision) Computer Science::Computer Vision and Pattern Recognition 020201 artificial intelligence & image processing Artificial intelligence Noise (video) business Rotation (mathematics) |
| Zdroj: | EAI Endorsed Transactions on Internet of Things, Vol 4, Iss 16 (2018) |
| ISSN: | 2414-1399 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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