Image restoration is of considerable interest in numerous scientific applications. When the image formation system is space invariant and linear, the blurred noise-free image can be expressed as the convolution of the original image with a blurring function: if the latter is known, then the Fast Fourier Transform can be used to efficiently compute convolutions. The algorithm presented here tries to remove the blur, using a priori constraints, without the knowledge of the blurring function. This approach is often referred to as Blind Deconvolution and finds useful applications, in particular, in astronomical imaging, in which the atmosphere of the Earth and the instruments of observation constitute sources of distortion and aberration that cannot be quantified in advance.
Blind Restoration of Astronomical Images
SPALETTA, GIULIA;
2005
Abstract
Image restoration is of considerable interest in numerous scientific applications. When the image formation system is space invariant and linear, the blurred noise-free image can be expressed as the convolution of the original image with a blurring function: if the latter is known, then the Fast Fourier Transform can be used to efficiently compute convolutions. The algorithm presented here tries to remove the blur, using a priori constraints, without the knowledge of the blurring function. This approach is often referred to as Blind Deconvolution and finds useful applications, in particular, in astronomical imaging, in which the atmosphere of the Earth and the instruments of observation constitute sources of distortion and aberration that cannot be quantified in advance.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
