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 un...
—We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson–Gau...
We propose a novel denoising algorithm to reduce the Poisson noise that is typically dominant in fluorescence microscopy data. To process large datasets at a low computational co...
The techniques described in this paper allow multiscale photon-limited image reconstruction methods to be implemented with significantly less computational complexity than previou...
We consider a two-dimensional problem of positron emission tomography where the random mechanism of the generation of the tomographic data is modeled by Poisson processes. The goa...