Lens distortion correction and enhancement based on local self-similarity for high-quality consumer imaging systems
| Autor: | Donggyun Kim, Tae-Chan Kim, Junghoon Jung, Jinho Park, Joonki Paik |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
business.industry
Distortion (optics) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Tensor completion law.invention Lens (optics) Kernel (image processing) law Nonlinear distortion Resampling Media Technology Computer vision Artificial intelligence Electrical and Electronic Engineering business Image restoration ComputingMethodologies_COMPUTERGRAPHICS Interpolation Mathematics |
| Zdroj: | IEEE Transactions on Consumer Electronics. 60:18-22 |
| ISSN: | 0098-3063 |
| DOI: | 10.1109/tce.2014.6780920 |
| Popis: | In this paper, a novel image enhancement system for a wide-angle lens camera is presented. The proposed system consists of; i) lens distortion correction using space-varying interpolation kernels and ii) image restoration based on the local self-similarity. The correction process for the geometric distortion produced by a wide-angle lens results in radial distortion artifacts caused by non-linear resampling. To reduce such artifacts, the proposed algorithm uses space-varying interpolation kernels derived from the lens calibration data. The corrected image is further enhanced using self-example-based image restoration. Experimental results demonstrate the proposed method can correctly remove the geometric distortion and further enhance the quality of the radially interpolated image. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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