A New Algorithm for Super-Resolution from Image Sequences

Authors:
Fabien Dekeyser;Patrick Bouthemy;Patrick Pérez
Affiliations:
-;-;-
Venue:
CAIP '01 Proceedings of the 9th International Conference on Computer Analysis of Images and Patterns
Year:
2001

Citing 4
Cited 0

Super-Resolution from Image Sequences - A Review

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Artifact reduction for set theoretic super resolution image reconstruction with edge adaptive constraints and higher-order interpolants

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Abstract

This paper deals with super-resolution, i.e. the reconstruction of a high resolution image from a sequence of low resolution noisy and possibly blurred images. We have developed an iterative procedure for minimizing a measure of discrepancy based on the Csiszàr's I-divergence. One advantage of this algorithm is to provide a natural positivity constraint on the solution. We consider a block-based version to speed up convergence and we propose a computationally efficient implementation. We also introduce a temporal multiscale version of the algorithm, which proves to be more robust and stable. The algorithm requires the computation of the apparent motion in the image sequence. We use a robust multiresolution estimator of a 2D parametric motion model in order to keep computational efficiency.