NDLI: Empirical filter estimation for subpixel interpolation and matching

Content Provider	IEEE Xplore Digital Library
Author	Triggs, B.
Copyright Year	2001
Description	Author affiliation: INRIA, CNRS, Montbonnot, France (Triggs, B.)
Abstract	We study the low-level problem of predicting pixel intensities after subpixel image translations. This is a basic subroutine for image warping and super-resolution, and it has a critical influence on the accuracy of subpixel matching by image correlation. Rather than using traditional frequency-space filtering theory or ad hoc interpolators such as splines, we take an empirical approach, finding optimal subpixel interpolation filters by direct numerical optimization over a large set of training examples. The training set is generated by subsampling larger images at different translations, using subsamplers that mimic the spatial response functions of real pixels. We argue that this gives realistic results, and design filters of various different parametric forms under traditional and robust prediction error metrics. We systematically study the performance of the resulting filters, paying particular attention to the influence of the underlying image sampling regime and the effects of aliasing ("jaggies"). We summarize the results and give practical advice for obtaining subpixel accuracy.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Pattern Anal. & Machine Intelligence
Starting Page	550
Ending Page	557
File Size	1358091
Page Count	8
File Format	PDF
ISBN	0769511430
DOI	10.1109/ICCV.2001.937674
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-07-07
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Matched filters Interpolation Pixel Filtering theory Algorithms Spatial resolution Image resolution Frequency Robustness Image sampling
Content Type	Text
Resource Type	Article

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