M. Gunsay et Bd. Jeffs, POINT-SOURCE LOCALIZATION IN BLURRED IMAGES BY A FREQUENCY-DOMAIN EIGENVECTOR-BASED METHOD, IEEE transactions on image processing, 4(12), 1995, pp. 1602-1612
In this paper, we address the problem of resolving and localizing blur
red point sources in intensity images. Telescopic star-field images bl
urred by atmospheric turbulence or optical aberrations are typical exa
mples of this class of images. A new approach to image restoration is
introduced, which is a generalization of 2-D sensor array processing t
echniques originating from the field of direction of arrival estimatio
n (DOA). It is shown that in the frequency domain, blurred point sourc
e images can be modeled with a structure analogous to the response of
linear sensor arrays to coherent signal sources. Thus, the problem may
be cast into the form of DOA estimation, and eigenvector based subspa
ce decomposition algorithms, such as MUSIC, may be adapted to search f
or these point sources. For deterministic point images the signal subs
pace is degenerate, with rank one, so rank enhancement techniques are
required before MUSIC or related algorithms may be used. The presence
of blur prohibits use of existing rank enhancement methods. A generali
zed array smoothing method is introduced for rank enhancement in the p
resence of blur, and to regularize the ill posed nature of the image r
estoration. The new algorithm achieves inter pixel superresolution and
is computationally efficient. Examples of star image deblurring using
the algorithm are presented.