ieeexplore.ieee.org
On improving sub-pixel accuracy by means of B-Spline
Sandro R Fernandes, Vania V Estrela, Osamu Saotome
2014 IEEE International Conference on Imaging Systems and Techniques (IST) Proceedings, 68-72, 2014
Local perturbations nearby contours strongly perturb the final result of processing remotely sensed images (RSI). It is common to establish a priori data to aid the estimation process. One can move some steps forward by means of a deformable model, for example, the snake model. In up to date research, the deformable contour is represented via B-spline snakes, which allows local control, concise depiction, and the use of fewer parameters. The estimation of edges with sub-pixel accuracy via a global B-spline depiction depends on determining the edge according to a Maximum Likelihood (ML) agenda and using the observed information likelihood. This practice guarantees that outliers present in data will be cleaned out. The data likelihood is calculated as a result of the observation model comprising both orientation and position data. Experiments where this procedure and the traditional spline interpolation have revealed that the algorithm introduced outperforms the conventional method for Gaussian as well as Salt and Pepper noise.
%0 Journal Article
%1 Estrela2014
%A Fernandes, S.R.
%A Estrela, V.V.
%A Estrela, Vania Vieira
%A Saotome, O.
%D 2014
%J IST 2014 - 2014 IEEE International Conference on Imaging Systems and Techniques, Proceedings
%K GIS computer_vision earth_observation image_analysis image_processing imported multiresolution myown remote_sensing spatial_analysis subpixel super-resolution surveillance
%P 68-72
%R 10.1109/IST.2014.6958448
%T On improving sub-pixel accuracy by means of B-spline
%U https://ieeexplore.ieee.org/abstract/document/6958448/
%X ieeexplore.ieee.org
On improving sub-pixel accuracy by means of B-Spline
Sandro R Fernandes, Vania V Estrela, Osamu Saotome
2014 IEEE International Conference on Imaging Systems and Techniques (IST) Proceedings, 68-72, 2014
Local perturbations nearby contours strongly perturb the final result of processing remotely sensed images (RSI). It is common to establish a priori data to aid the estimation process. One can move some steps forward by means of a deformable model, for example, the snake model. In up to date research, the deformable contour is represented via B-spline snakes, which allows local control, concise depiction, and the use of fewer parameters. The estimation of edges with sub-pixel accuracy via a global B-spline depiction depends on determining the edge according to a Maximum Likelihood (ML) agenda and using the observed information likelihood. This practice guarantees that outliers present in data will be cleaned out. The data likelihood is calculated as a result of the observation model comprising both orientation and position data. Experiments where this procedure and the traditional spline interpolation have revealed that the algorithm introduced outperforms the conventional method for Gaussian as well as Salt and Pepper noise.
@article{Estrela2014,
abstract = {
ieeexplore.ieee.org
On improving sub-pixel accuracy by means of B-Spline
Sandro R Fernandes, Vania V Estrela, Osamu Saotome
2014 IEEE International Conference on Imaging Systems and Techniques (IST) Proceedings, 68-72, 2014
Local perturbations nearby contours strongly perturb the final result of processing remotely sensed images (RSI). It is common to establish a priori data to aid the estimation process. One can move some steps forward by means of a deformable model, for example, the snake model. In up to date research, the deformable contour is represented via B-spline snakes, which allows local control, concise depiction, and the use of fewer parameters. The estimation of edges with sub-pixel accuracy via a global B-spline depiction depends on determining the edge according to a Maximum Likelihood (ML) agenda and using the observed information likelihood. This practice guarantees that outliers present in data will be cleaned out. The data likelihood is calculated as a result of the observation model comprising both orientation and position data. Experiments where this procedure and the traditional spline interpolation have revealed that the algorithm introduced outperforms the conventional method for Gaussian as well as Salt and Pepper noise.},
added-at = {2021-04-21T11:45:34.000+0200},
author = {Fernandes, S.R. and Estrela, V.V. and Estrela, Vania Vieira and Saotome, O.},
biburl = {https://www.bibsonomy.org/bibtex/2632a5020af560bfdca0ff2fdde08703b/vaniave},
doi = {10.1109/IST.2014.6958448},
interhash = {48b9316f3b7a47b72ac47de15211b8bb},
intrahash = {632a5020af560bfdca0ff2fdde08703b},
journal = {IST 2014 - 2014 IEEE International Conference on Imaging Systems and Techniques, Proceedings},
keywords = {GIS computer_vision earth_observation image_analysis image_processing imported multiresolution myown remote_sensing spatial_analysis subpixel super-resolution surveillance},
language = {English},
pages = {68-72},
timestamp = {2021-05-16T21:57:06.000+0200},
title = {On improving sub-pixel accuracy by means of B-spline},
url = {https://ieeexplore.ieee.org/abstract/document/6958448/},
year = 2014
}