DocumentCode
1187421
Title
Approximating filtered scale-variant signals
Author
Bovik, Alan Conrad ; Raj, Raghu G.
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Texas, Austin, TX, USA
Volume
14
Issue
1
fYear
2005
Firstpage
23
Lastpage
35
Abstract
We develop theorems that place limits on the point-wise approximation of the responses of filters, both linear shift invariant (LSI) and linear shift variant (LSV), to input signals and images that are LSV in the following sense: they can be expressed as the outputs of systems with LSV impulse responses, where the shift variance is with respect to the filter scale of a single-prototype filter. The approximations take the form of LSI approximations to the responses. We develop tight bounds on the approximation errors expressed in terms of filter durations and derivative (Sobolev) norms. Finally, we find application of the developed theory to defoveation of images, deblurring of shift-variant blurs, and shift-variant edge detection.
Keywords
approximation theory; filtering theory; signal processing; approximation error; filtered scale-variant signal approximation; image defoveation; linear shift invariant; linear shift variant; pointwise approximation; shift-invariant blur deblurring; shift-invariant edge detection; Approximation error; Biological system modeling; Continuous wavelet transforms; Convolution; Filtering; Kernel; Laboratories; Large scale integration; Nonlinear filters; Signal processing; Algorithms; Artificial Intelligence; Computer Graphics; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Models, Statistical; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2004.838696
Filename
1369327
Link To Document