Wavelet denoising of multiframe optical coherence tomography data
We introduce a novel speckle noise reduction algorithm for OCT images. Contrary to present approaches, the algorithm does not rely on simple averaging of multiple image frames or denoising on the final averaged image. Instead it uses wavelet decompositions of the single frames for a local noise and...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
22 February 2012
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| In: |
Biomedical optics express
Year: 2012, Volume: 3, Issue: 3, Pages: 572-589 |
| ISSN: | 2156-7085 |
| DOI: | 10.1364/BOE.3.000572 |
| Online Access: | Verlag, Volltext: http://dx.doi.org/10.1364/BOE.3.000572 Verlag, Volltext: https://www.osapublishing.org/boe/abstract.cfm?uri=boe-3-3-572 
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| Author Notes: | Markus A. Mayer, Anja Borsdorf, Martin Wagner, Joachim Hornegger, Christian Y. Mardin, and Ralf P. Tornow |
| Summary: | We introduce a novel speckle noise reduction algorithm for OCT images. Contrary to present approaches, the algorithm does not rely on simple averaging of multiple image frames or denoising on the final averaged image. Instead it uses wavelet decompositions of the single frames for a local noise and structure estimation. Based on this analysis, the wavelet detail coefficients are weighted, averaged and reconstructed. At a signal-to-noise gain at about 100% we observe only a minor sharpness decrease, as measured by a full-width-half-maximum reduction of 10.5%. While a similar signal-to-noise gain would require averaging of 29 frames, we achieve this result using only 8 frames as input to the algorithm. A possible application of the proposed algorithm is preprocessing in retinal structure segmentation algorithms, to allow a better differentiation between real tissue information and unwanted speckle noise. |
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| Item Description: | Gesehen am 05.11.2018 |
| Physical Description: | Online Resource |
| ISSN: | 2156-7085 |
| DOI: | 10.1364/BOE.3.000572 |