Title :
Image reconstruction from projections under wavelet constraints
Author :
Sahiner, Berkman ; Yagle, Andrew E.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
fDate :
12/1/1993 12:00:00 AM
Abstract :
First, the authors discuss how the wavelet transform can be used to perform spatially-varying filtering of an image, suppressing noise locally in smooth regions of the image, and discuss detection of such regions in a noise-corrupted image. Second, they show how to compute the minimum mean-square estimate of an image given: (1) noisy projections of the image; (2) statistics of additive noise in the projections; and (3) constraints on wavelet coefficients of the image. Examples illustrate the resulting procedure
Keywords :
filtering and prediction theory; image reconstruction; interference suppression; least squares approximations; spatial filters; wavelet transforms; additive noise; minimum mean-square estimate; noise suppression; noise-corrupted image; noisy projections; projections; smooth regions; spatially-varying filtering; wavelet constraints; wavelet transform; Filtering; Image coding; Image reconstruction; Low pass filters; Signal processing; Signal processing algorithms; Signal resolution; Signal to noise ratio; Spatial resolution; Speech processing;
Journal_Title :
Signal Processing, IEEE Transactions on
