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1736 IEEE TRANSACTIONS ON ACOUSTICS,SPEECH, ANDSIGNAL PROCESSING, VOL. ASSP-35,NO. 12, DECEMBER 1987 Two-Dimensional Block Kalman Filtering for Image
 

Summary: 1736 IEEE TRANSACTIONS ON ACOUSTICS,SPEECH, ANDSIGNAL PROCESSING, VOL. ASSP-35,NO. 12, DECEMBER 1987
Two-Dimensional Block Kalman Filtering for Image
Restoration
Abstract-This paper is concerned with developing an efficient two-
dimensional (2-D) block Kalman filtering for digital image restoration.
A new 2-D multiinput, multioutput (MIMO) state-space structure for
modeling the image generation process is introduced. This structure is
derived by arranging a vector autoregressive (AR) model with a causal
quarter-plane region of support in block form. This model takes into
account the correlations of the image data in successive neighboring
blocks and, as a result, reduces the edge effects prominent in the avail-
able Kalmau strip filtering techniques. The degradation model for an
infinite extent Linear space invariant (LSI) blur and white Gaussian
(WG) noise is also modeled by an MIMO block state-space equation
stemmed from a single-input single-output (SISO) 2-D state-space
structure. The image generation model and the degradation model are
combinedto yield a composite block-state dynamic structure. The block
Kalman filtering equations are obtained for this dynamic structure and
then used to compute the suboptimal filter estimates of a noisy and
blurred image.

  

Source: Azimi-Sadjadi, Mahmood R. - Department of Electrical and Computer Engineering, Colorado State University

 

Collections: Computer Technologies and Information Sciences