A feature-based technique for joint, linear estimation ofhigh-order image-to-mosaic transformations: mosaicing the curved humanretina
Can, A.
Stewart, C.V.
Roysam, B.
Tanenbaum, H.L.
Dept. of Electr. Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Mar 2002
Volume: 24,
Issue: 3
On page(s): 412-419
ISSN: 0162-8828
References Cited: 31
CODEN: ITPIDJ
INSPEC Accession Number: 7223264
Digital Object Identifier: 10.1109/34.990145
Current Version Published: 2002-08-07
Abstract
An algorithm for constructing image mosaics from multiple,
uncalibrated, weak-perspective views of the human retina is presented
and analyzed. It builds on an algorithm for registering pairs of retinal
images using a noninvertible, 12-parameter, quadratic image
transformation model and hierarchical, robust estimation. The major
innovation presented is a linear, feature-based, noniterative method for
jointly estimating consistent transformations of all images onto the
mosaic "anchor image." Constraints for this estimation are derived from
pairwise registration both directly with the anchor image and indirectly
between pairs of nonanchor images. An incremental, graph-based technique
constructs the set of registered image pairs used in the solution. The
estimation technique allows images that do not overlap the anchor frame
to be successfully mosaiced, a valuable capability for mosaicing images
of the retinal periphery. Experimental analysis on data sets from 16
eyes shows the average overall median transformation error in final
mosaic to be 0.76 pixels. The technique is simpler, more accurate, and
offers broader coverage than previously published methods
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