Undecimated Haar Thresholding For Poisson Intensity Estimation

We propose a novel algorithm for denoising Poisson-corrupted images, that performs a signal-adaptive thresholding of the undecimated Haar wavelet coefficients. A Poisson's unbiased MSE estimate is devised and adapted to arbitrary transform-domain pointwise processing. This prior-free quadratic measure of quality is then used to globally optimize a linearly parameterized subband-adaptive thresholding, which accounts for the signal-dependent noise variance. We demonstrate the qualitative and computational competitiveness of the resulting denoising algorithm through comprehensive comparisons with some state-of-the-art multiscale techniques specifically designed for Poisson intensity estimation. We also show promising denoising results obtained on low-count fluorescence microscopy images.


Published in:
2010 Ieee International Conference On Image Processing, 1697-1700
Presented at:
IEEE International Conference on Image Processing, Hong Kong, PEOPLES R CHINA, Sep 26-29, 2010
Year:
2010
Publisher:
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa
ISBN:
978-1-4244-7994-8
Keywords:
Laboratories:




 Record created 2011-12-16, last modified 2018-03-17

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