Noise and Signal Activity Maps for Better Imaging Algorithms

Abstract

In this work, we propose noise and signal activity estimation method that discriminates noise from signal based on local and global properties of the image data. The method yields pixel-wise maps of the noise variance and of the signal activity. Using these maps to guide imaging algorithms such as image enhancement and print defect detection improves their performance. The proposed method does not assume a white Gaussian noise model; it is very efficient computationally and, as such, is useful for a wide variety of applications.