A spatially adaptive Poissonian image deblurring

A spatially adaptive image deblurring algorithm is presented for Poisson observations. It adapts to the unknown image smoothness by using local polynomial approximation (LPA) kernel estimates of varying scale and direction based on the intersection of con?dence intervals (ICI) rule. The signal-dependant characteristics of the Poissonian noise are exploited to accurately compute the pointwise variances of the directional estimates. The results show that this accurate pointwise adaptive algorithm signi?cantly improves the image restoration quality.

• Type: Conference
• Year: 2005
• Where: ICIP
• Authors: Alessandro Foi, Sakari Alenius, Mejdi Trimeche, Vladimir Katkovnik, Karen O. Egiazarian
• Keywords: ICIP 2005, Image Deblurring Algorithm, Image Processing, Image Restoration Quality, Pointwise Adaptive Algorithm, Pointwise Variances, Unknown Image Smoothness