Structure tensor‐based SIFT algorithm for SAR image registration
| Autor: | Divya S, Sourabh Paul, Umesh C. Pati |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Synthetic aperture radar
Matching (graph theory) Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image registration Scale-invariant feature transform 02 engineering and technology Structure tensor Radar imaging 0202 electrical engineering electronic engineering information engineering Computer vision Electrical and Electronic Engineering skin and connective tissue diseases business.industry fungi 020206 networking & telecommunications Speckle noise body regions Computer Science::Graphics Computer Science::Computer Vision and Pattern Recognition Signal Processing 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence business Software |
| Zdroj: | IET Image Processing. 14:929-938 |
| ISSN: | 1751-9667 |
| DOI: | 10.1049/iet-ipr.2019.0568 |
| Popis: | The scale-invariant feature transform (SIFT) algorithm is the most widely used feature extraction as well as a feature matching method in remote sensing image registration. However, the performance of this algorithm is affected by the influence of speckle noise in synthetic aperture radar (SAR) images. It reduces the number of correct matches as well as the correct matching rate in SAR image registration. Moreover, SAR image registration is considered to be a challenging task as the images generally have significant geometric as well as intensity variations. To address these problems, a structure tensor-based SIFT algorithm is proposed to register the SAR images. At first, the tensor diffusion technique is used to construct the scale layers. Then, the features are extracted in the scale layers. Finally, feature matching is performed between the input SAR images and correct matches are identified. The proposed method can increase the number of correct matches as well as position accuracy in registration. Experiments have been conducted on five SAR image pairs to verify the effectiveness of the method. |
| Databáze: | OpenAIRE |
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