Mayer MA, Borsdorf A, Wagner M, Hornegger J, Mardin CY, Tornow RP (2012)
Publication Type: Journal article, Original article
Publication year: 2012
Original Authors: Mayer M., Borsdorf A., Wagner M., Hornegger J., Mardin C., Tornow R.
Publisher: Optical Society of America
Book Volume: 3
Pages Range: 572-589
Journal Issue: 3
DOI: 10.1364/BOE.3.000572
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. © 2012 Optical Society of America.
APA:
Mayer, M.A., Borsdorf, A., Wagner, M., Hornegger, J., Mardin, C.Y., & Tornow, R.-P. (2012). Wavelet denoising of multi frame optical coherence tomography data. Biomedical Optics Express, 3(3), 572-589. https://doi.org/10.1364/BOE.3.000572
MLA:
Mayer, Markus Anton, et al. "Wavelet denoising of multi frame optical coherence tomography data." Biomedical Optics Express 3.3 (2012): 572-589.
BibTeX: Download