Anisotropic spectral magnitude estimation filters for noise reduction and image enhancement

Describes an algorithm for noise reduction and enhancement of images which is able to take into account anisotropies of signal as well as of noise. Processing is based on subjecting each image to a block DFT, followed by comparing each observed magnitude coefficient to the expected noise standard deviation for it. Depending on this comparison, each coefficient is attenuated the more, the more likely it is that it contains only noise. In addition, the attenuation is made dependent on whether or not the observed coefficient contributes to an oriented prominent structure within the processed image block. Orientation as well as the distinctness with which it occurs are detected in the spectral domain by an inertia-like matrix. Orientation information is additionally exploited to selectively enhance oriented structures, thus only marginally increasing noise as compared to isotropic enhancement.