Description: Despite its practical importance in image processing
and computer vision, blind blur identification and blind image
restoration have so far been addressed under restrictive assumptions
such as all-pole stationary image models blurred by zero- or
minimum-phase point-spread functions. Relying upon diversity
(availability of a sufficient number of multiple blurred images),
we develop blind FIR blur identification and order determination
schemes. Apart from a minimal persistence of excitation condition
(also present with nonblind setups), the inaccessible input image
is allowed to be deterministic or random and of unknown color or
distribution. With the blurs satisfying a certain co-primeness condition
in addition, we establish existence and uniqueness results
which guarantee that single-input/multiple-output FIR blurred
images can be restored blindly, though perfectly in the absence of
noise, using linear FIR filters. Results of simulations employing
the blind order determi
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BID of Multichannel and Perfect Image Restoration.pdf
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