Distortion adaptive Sobel filters for the gradient estimation of wide angle images
| Autor: | Antonino Furnari, Sebastiano Battiato, Arcangelo Ranieri Bruna, Giovanni Maria Farinella |
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| Rok vydání: | 2017 |
| Předmět: |
Wide angle images
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Normalization (image processing) 02 engineering and technology Gradient estimation Web page 0202 electrical engineering electronic engineering information engineering Media Technology Computer vision Electrical and Electronic Engineering Mathematics business.industry Distortion (optics) Geometric transformation 020207 software engineering Sobel operator Real image Adaptive filter Computer Science::Computer Vision and Pattern Recognition Adaptive filters Signal Processing 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence business |
| Zdroj: | Journal of Visual Communication and Image Representation. 46:165-175 |
| ISSN: | 1047-3203 |
| Popis: | We introduce a set of distortion adaptive Sobel filters for the direct estimation of geometrically correct gradients of wide angle images. The definition of the filters is based on Sobel’s rationale and accounts for the geometric transformation undergone by wide angle images due to the presence of radial distortion. Moreover, we show that a local normalization of the filters magnitude is essential to achieve state-of-the-art results. To perform the experimental analysis, we propose an evaluation pipeline and a benchmark dataset of images belonging to different scene categories. Experiments on both, synthetic and real images, show that our approach outperforms the current state-of-the-art in both gradient estimation and keypoint matching for images characterized by large amounts of radial distortion. The collected dataset and the MATLAB code of the proposed method can be downloaded at our web page http://iplab.dmi.unict.it/DASF/ . |
| Databáze: | OpenAIRE |
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