Centi-pixel accurate real-time inverse distortion correction
| Autor: | R. Geldenhuys, F. Wilhelm Leuschner, Jason P. de Villiers |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Pixel
business.industry Computer science Distortion (optics) Data_MISCELLANEOUS ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) Inverse Image (mathematics) law.invention Lens (optics) law Position (vector) Computer Science::Computer Vision and Pattern Recognition Computer data storage business Algorithm |
| Zdroj: | SPIE Proceedings. |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.804771 |
| Popis: | Inverse distortion is used to create an undistorted image from a distorted image. For each pixel in the undistorted image it is required to determine which pixel in the distorted image should be used. However the process of characterizing a lens using a model such as that of Brown, yields a non-invertible mapping from the distorted domain to the undistorted domain. There are three current approaches to solving this: an approximation of the inverse distortion is derived from a low-order version of Brown's model; an initial guess for the distorted position is iteratively refined until it yields the desired undistorted pixel position; or a look-up table is generated to store the mapping. Each approach requires one to sacrifice either accuracy, memory usage or processing time. This paper shows that it is possible to have real-time, low memory, accurate inverse distortion correction. A novel method based on the re-use of left-over distortion characterization data is combined with modern numerical optimization techniques to fit a high-order version of Brown's model to characterize the inverse distortion. Experimental results show that, for thirty-two 5mm lenses exhibiting extreme barrel distortion, inverse distortion can be improved 25 fold to 0.013 pixels RMS over the image. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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