Wavelet denoising of poisson-distributed data and applications
Computational Statistics & Data Analysis
MMSE Filtering of generalised signal-dependent noise in spatial and shift-invariant wavelet domains
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
Fast interscale wavelet denoising of Poisson-corrupted images
Signal Processing
Development of EMD-based denoising methods inspired by wavelet thresholding
IEEE Transactions on Signal Processing
IEEE Transactions on Image Processing
Novel color demosaicking for noisy color filter array data
Signal Processing
Noise suppression in low-light images through joint denoising and demosaicing
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Multiscale modeling and estimation of Poisson processes with application to photon-limited imaging
IEEE Transactions on Information Theory
Multiscale Poisson Intensity and Density Estimation
IEEE Transactions on Information Theory
Wavelet-domain filtering for photon imaging systems
IEEE Transactions on Image Processing
Bayesian tree-structured image modeling using wavelet-domain hidden Markov models
IEEE Transactions on Image Processing
Image denoising using scale mixtures of Gaussians in the wavelet domain
IEEE Transactions on Image Processing
Improved Poisson intensity estimation: denoising application using Poisson data
IEEE Transactions on Image Processing
Joint demosaicing and denoising
IEEE Transactions on Image Processing
Image denoising using total least squares
IEEE Transactions on Image Processing
Wavelets, Ridgelets, and Curvelets for Poisson Noise Removal
IEEE Transactions on Image Processing
Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data
IEEE Transactions on Image Processing
Image Denoising in Mixed Poisson–Gaussian Noise
IEEE Transactions on Image Processing
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In this paper, we present a noise parameter estimation method using a simplified signal-dependent noise model. The generic Poisson-Gaussian noise model is simplified to a Gaussian-Gaussian noise model. From the simplified noise model, we experimentally verify that the value obtained by the robust median estimator is almost the same as the mean of the noise standard deviation. Based on this property, the noise model parameters are estimated by the least square method. Simulation results show that the estimation performance using our proposed algorithm is compatible with the performance of the existing method. Our method can generate good parameter estimation results with reduced computational complexity.