Error-Bounded and Adaptive Image Reconstruction
Raghu Machiraju, Edward Swan, and Roni Yagel. Error-Bounded and Adaptive Image Reconstruction. Technical Report OSU-CISRC-1/95-TR03, Ohio State University, 1995.
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Abstract
Reconstruction is imperative whenever an image needs to be resampled as a result of transformation such as an affine or perspective transform, or texture mapping. We present a new method for the characterization and measurement of reconstruction error. Our method, based on spatial domain error analysis, uses approximation theory to develop error bounds. We provide, for the first time, an efficient way to guarantee an error bound at every point by varying filter size. We go further to support position-adaptive and data-adaptive reconstruction which adjust filter size to the location of reconstruction and the data in its vicinity. We demonstrate the effectiveness of our methods with 1D and 2D examples.
BibTeX
@TechReport{TR95-ebair,
author = {Raghu Machiraju and Edward Swan and Roni Yagel},
title = {Error-Bounded and Adaptive Image Reconstruction},
institution = {Ohio State University},
type = {Technical Report},
number = {OSU-CISRC-1/95-TR03},
month = {January},
year = 1995,
abstract = {
Reconstruction is imperative whenever an image needs to be resampled as a result
of transformation such as an affine or perspective transform, or texture
mapping. We present a new method for the characterization and measurement of
reconstruction error. Our method, based on spatial domain error analysis, uses
approximation theory to develop error bounds. We provide, for the first time, an
efficient way to guarantee an error bound at every point by varying filter
size. We go further to support position-adaptive and data-adaptive
reconstruction which adjust filter size to the location of reconstruction and
the data in its vicinity. We demonstrate the effectiveness of our methods with
1D and 2D examples.
},
}