Registration of infrared and visible light image based on visual saliency and scale invariant feature transform
Abstract Visual saliency is a type of visual feature which simulates visual attention selection mechanism in biological system and has better robustness and invariance. A rapid infrared image and visible light image registration method based on visual saliency and SIFT (scale invariant feature trans...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2018-06-01
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| Series: | EURASIP Journal on Image and Video Processing |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13640-018-0283-9 |
| _version_ | 1818542706973999104 |
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| author | Gang Liu Zhonghua Liu Sen Liu Jianwei Ma Fei Wang |
| author_facet | Gang Liu Zhonghua Liu Sen Liu Jianwei Ma Fei Wang |
| author_sort | Gang Liu |
| collection | DOAJ |
| description | Abstract Visual saliency is a type of visual feature which simulates visual attention selection mechanism in biological system and has better robustness and invariance. A rapid infrared image and visible light image registration method based on visual saliency and SIFT (scale invariant feature transform) is proposed in this paper. The method adopts amplitude modulation Fourier transform to construct saliency map, and the image salient points are achieved preliminarily by salient threshold. Subsequently, this method calculates the local entropy for these salient points because of entropy’s character for information measurement, then these points are reordered and screened based on the strategy of entropy priority. The screened results are thought as centers for salient regions. Morphological operation is used for growing and merging for neighbor salient scene region in image. Aiming at the abstracted salient region for image, PCA (principal component analysis)-SIFT algorithm is proposed, which can produce the compressed SIFT registration features and largely reduce the computational cost of image registration. The proposed algorithm adopts random sampling conformance method to remove the mistaken point pairs before calculating the model parameter of affine transformation for registration between infrared image and visible lights. The experimental results indicate that the method has good invariance under image scale, rotation, translation, and illumination variation and can realize effective registration between infrared image and visible lights. Compared with some classical algorithms, the proposed method has advantage in registration accuracy and registration speed obviously. |
| first_indexed | 2024-12-11T22:25:39Z |
| format | Article |
| id | doaj.art-1072ab4aa1e34a598b2f3dc3a1cf4b8f |
| institution | Directory Open Access Journal |
| issn | 1687-5281 |
| language | English |
| last_indexed | 2024-12-11T22:25:39Z |
| publishDate | 2018-06-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Image and Video Processing |
| spelling | doaj.art-1072ab4aa1e34a598b2f3dc3a1cf4b8f2022-12-22T00:48:18ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-52812018-06-012018111210.1186/s13640-018-0283-9Registration of infrared and visible light image based on visual saliency and scale invariant feature transformGang Liu0Zhonghua Liu1Sen Liu2Jianwei Ma3Fei Wang4Information Engineering College, Henan University of Science and TechnologyInformation Engineering College, Henan University of Science and TechnologyInformation Engineering College, Henan University of Science and TechnologyInformation Engineering College, Henan University of Science and TechnologyInformation Engineering College, Henan University of Science and TechnologyAbstract Visual saliency is a type of visual feature which simulates visual attention selection mechanism in biological system and has better robustness and invariance. A rapid infrared image and visible light image registration method based on visual saliency and SIFT (scale invariant feature transform) is proposed in this paper. The method adopts amplitude modulation Fourier transform to construct saliency map, and the image salient points are achieved preliminarily by salient threshold. Subsequently, this method calculates the local entropy for these salient points because of entropy’s character for information measurement, then these points are reordered and screened based on the strategy of entropy priority. The screened results are thought as centers for salient regions. Morphological operation is used for growing and merging for neighbor salient scene region in image. Aiming at the abstracted salient region for image, PCA (principal component analysis)-SIFT algorithm is proposed, which can produce the compressed SIFT registration features and largely reduce the computational cost of image registration. The proposed algorithm adopts random sampling conformance method to remove the mistaken point pairs before calculating the model parameter of affine transformation for registration between infrared image and visible lights. The experimental results indicate that the method has good invariance under image scale, rotation, translation, and illumination variation and can realize effective registration between infrared image and visible lights. Compared with some classical algorithms, the proposed method has advantage in registration accuracy and registration speed obviously.http://link.springer.com/article/10.1186/s13640-018-0283-9Image registrationInfrared and visible lightVisual saliencyScale invariant feature transformPrincipal component analysis |
| spellingShingle | Gang Liu Zhonghua Liu Sen Liu Jianwei Ma Fei Wang Registration of infrared and visible light image based on visual saliency and scale invariant feature transform EURASIP Journal on Image and Video Processing Image registration Infrared and visible light Visual saliency Scale invariant feature transform Principal component analysis |
| title | Registration of infrared and visible light image based on visual saliency and scale invariant feature transform |
| title_full | Registration of infrared and visible light image based on visual saliency and scale invariant feature transform |
| title_fullStr | Registration of infrared and visible light image based on visual saliency and scale invariant feature transform |
| title_full_unstemmed | Registration of infrared and visible light image based on visual saliency and scale invariant feature transform |
| title_short | Registration of infrared and visible light image based on visual saliency and scale invariant feature transform |
| title_sort | registration of infrared and visible light image based on visual saliency and scale invariant feature transform |
| topic | Image registration Infrared and visible light Visual saliency Scale invariant feature transform Principal component analysis |
| url | http://link.springer.com/article/10.1186/s13640-018-0283-9 |
| work_keys_str_mv | AT gangliu registrationofinfraredandvisiblelightimagebasedonvisualsaliencyandscaleinvariantfeaturetransform AT zhonghualiu registrationofinfraredandvisiblelightimagebasedonvisualsaliencyandscaleinvariantfeaturetransform AT senliu registrationofinfraredandvisiblelightimagebasedonvisualsaliencyandscaleinvariantfeaturetransform AT jianweima registrationofinfraredandvisiblelightimagebasedonvisualsaliencyandscaleinvariantfeaturetransform AT feiwang registrationofinfraredandvisiblelightimagebasedonvisualsaliencyandscaleinvariantfeaturetransform |