Automatically Adjustable Real-Time Capable Noise Filtering in Image Processing
Gabiger-Rose A, Kube M, Schmitt P, Weigel R (2011)
Publication Type: Conference contribution
Publication year: 2011
Conference Proceedings Title: Embedded World
Event location: Nuremberg, Germany
Abstract
In this work, a way to achieve the best noise suppression in images while preserving the spatial resolution is presented. The noise filtering is done by means of a bilateral filter. The denotation bilateral filtering suggests the combination of domain and range filtering. The domain filter averages the nearby pixel values and acts thereby as a low-pass filter. The range filter stands for the nonlinear component and plays an important part in edge preserving. Both filtering components can be adjusted by according parameters. In this work the way is presented, how the adjustment parameter for the nonlinear photometric component of the filter can be derived from the noise standard deviation, which allows the highest PSNR increase while retaining the structural similarity index at high level. The noise statistics is measured during the initialization of the camera and stored for the filtering purpose. Using the presented instruction for the calculation of the adjustment parameter of the photometric component an automatical adjustment of the noise filter is possible, whereas the adjustment can be done for any noise standard deviation. It is shown, that utilizing the instruction for the automatical adjustment of the noise filter the noise suppression without a loss of structural information is achievable at any noise level.
Authors with CRIS profile
Anna Gabiger-Rose
Lehrstuhl für Technische Elektronik
Robert Weigel
Lehrstuhl für Technische Elektronik
Involved external institutions
Germany (DE)How to cite
APA:
Gabiger-Rose, A., Kube, M., Schmitt, P., & Weigel, R. (2011). Automatically Adjustable Real-Time Capable Noise Filtering in Image Processing. In Embedded World. Nuremberg, Germany.
MLA:
Gabiger-Rose, Anna, et al. "Automatically Adjustable Real-Time Capable Noise Filtering in Image Processing." Proceedings of the Embedded World, Nuremberg, Germany 2011.
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