An Improved Observation Model for Super-Resolution Under Affine Motion

• Published in: IEEE transactions on image processing Vol. 15; no. 11; pp. 3325 - 3337
• Main Authors: Rochefort, G., Champagnat, F., Le Besnerais, G., Giovannelli, J.-F.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.2006; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Affine motion; Airborne sensing; Algorithms; Applied sciences; Artificial Intelligence; bspline; Computer Simulation; Context modeling; convex regularization; Detection, estimation, filtering, equalization, prediction; Equivalence; Exact sciences and technology; Frames; High-resolution imaging; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image processing; Image reconstruction; Image resolution; Image sensors; Image sequences; Information Storage and Retrieval - methods; Information, signal and communications theory; Interpolation; Inverse problems; Mathematical models; Models, Theoretical; Motion; Motion estimation; multipass interpolation; projection; Reconstruction; Reproducibility of Results; Sensitivity and Specificity; Signal and communications theory; Signal processing; Signal, noise; Strontium; Subtraction Technique; super-resolution; Telecommunications and information theory; Transforms; Video Recording - methods; Isometry; Image resolution; Superresolution; super-resolution; convex regularization; L2 approximation; Affine transformation; Implementation; Inverse problem; bspline; Image quality; Interpolation; Affine motion; Image sequence; Imaging; inverse problems; projection; multipass interpolation
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2006.881996

Super-resolution (SR) techniques make use of subpixel shifts between frames in an image sequence to yield higher resolution images. We propose an original observation model devoted to the case of nonisometric inter-frame motion as required, for instance, in the context of airborne imaging sensors. First, we describe how the main observation models used in the SR literature deal with motion, and we explain why they are not suited for nonisometric motion. Then, we propose an extension of the observation model by Elad and Feuer adapted to affine motion. This model is based on a decomposition of affine transforms into successive shear transforms, each one efficiently implemented by row-by-row or column-by-column one-dimensional affine transforms. We demonstrate on synthetic and real sequences that our observation model incorporated in a SR reconstruction technique leads to better results in the case of variable scale motions and it provides equivalent results in the case of isometric motions