EM-based estimation of spatially variant correlated image noise

Bart Goossens, Aleksandra Pizurica, Wilfried Philips
2008 2008 15th IEEE International Conference on Image Processing  
In image denoising applications, noise is often correlated and the noise energy and correlation structure may even vary with the position in the image. Existing noise reduction and estimation methods are usually designed for stationary white Gaussian noise and generally work less efficient in this case because of the noise model mismatch. In this paper, we propose an EM algorithm for the estimation of spatially variant (nonstationary) correlated image noise in the wavelet domain. In particular,
more » ... ain. In particular, we study additive white Gaussian noise filtered by a space-variant linear filter. This general noise model is applicable to a wide variety of practical situations, including noise in Computed Tomography (CT). Results demonstrate the effectiveness of the proposed solution and its robustness to signal structures.
doi:10.1109/icip.2008.4712112 dblp:conf/icip/GoossensPP08 fatcat:42oocgy2nvb25cujb6zg4c4fau