Efficient image warping and super-resolution
Ming-Chao Chiang
Boult, T.E.
Dept. of Comput. Sci., Columbia Univ., New York, NY;
This paper appears in: Applications of Computer Vision, 1996. WACV '96., Proceedings 3rd IEEE Workshop on
Publication Date: 2-4 Dec 1996
On page(s): 56-61
Meeting Date: 12/02/1996 - 12/04/1996
Location: Sarasota, FL, USA
ISBN: 0-8186-7620-5
References Cited: 12
INSPEC Accession Number: 5485088
Digital Object Identifier: 10.1109/ACV.1996.572000
Current Version Published: 2002-08-06
Abstract
This paper introduces a new algorithm for enhancing image
resolution from an image sequence. The approach we propose herein uses
the integrating resampler proposed by M. Chiang and T. Boult (1996) as
the underlying resampling algorithm. Moreover, it is a direct method,
which is fundamentally different from the iterative, back-projection
approaches proposed in previous work. We show that image warping
techniques may have a strong impact on the quality of image resolution
enhancement. By coupling the degradation model of the imaging system
directly into the integrating resampler, we can better approximate the
warping characteristics of real sensors, which also highly improve the
quality of super-resolution images. Examples of super-resolutions are
given for gray-scale images. Evaluations are made by comparing the
resulting images and those using bi-linear resampling and
back-projection. Results from our experiments show that integrating
resampler outperforms traditional bi-linear resampling
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