An Improved Calibration Technique for Polarization Images
Polarization imaging can be used to improve the image quality by reducing the effects of the unwanted light reflection, enhancing the quality of images taken in non-ideal conditions, such as foggy weather, or reconstructing the 3D form of an object based on the shape from polarization. Reconstructin...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8648346/ |
| _version_ | 1818618027603656704 |
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| author | Eri Prasetyo Wibowo Aini Suri Talita Mohammad Iqbal Achmad Benny Mutiara Cheng-Kai Lu Fabrice Meriaudeau |
| author_facet | Eri Prasetyo Wibowo Aini Suri Talita Mohammad Iqbal Achmad Benny Mutiara Cheng-Kai Lu Fabrice Meriaudeau |
| author_sort | Eri Prasetyo Wibowo |
| collection | DOAJ |
| description | Polarization imaging can be used to improve the image quality by reducing the effects of the unwanted light reflection, enhancing the quality of images taken in non-ideal conditions, such as foggy weather, or reconstructing the 3D form of an object based on the shape from polarization. Reconstructing a 3D form requires the acquisition of multiple images and inference of the polarization parameters, such as the degree of polarization and angle of polarization, from these experimental data. The light polarization extraction process should begin by performing the photometric calibration to improve the performance of the polarize instrument measurements by reducing the measurement errors and improving the consistency between measurements. We propose an algorithm based on the kernel ridge regression method to estimate both the polarization parameters and the measurement (angle) errors in the placement of the polarizer. The algorithm was tested on four different sets of images containing different objects based on their responses to light and polarization. The algorithm that uses the mixed kernel function gives the best results. |
| first_indexed | 2024-12-16T17:15:04Z |
| format | Article |
| id | doaj.art-77abd5b3db884bc8973e92bf27ffc474 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T17:15:04Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-77abd5b3db884bc8973e92bf27ffc4742022-12-21T22:23:18ZengIEEEIEEE Access2169-35362019-01-017286512866210.1109/ACCESS.2019.29005388648346An Improved Calibration Technique for Polarization ImagesEri Prasetyo Wibowo0Aini Suri Talita1Mohammad Iqbal2Achmad Benny Mutiara3Cheng-Kai Lu4https://orcid.org/0000-0002-5819-0754Fabrice Meriaudeau5Faculty of Computer Science and Information Technology, Gunadarma University, Jakarta, IndonesiaFaculty of Computer Science and Information Technology, Gunadarma University, Jakarta, IndonesiaFaculty of Computer Science and Information Technology, Gunadarma University, Jakarta, IndonesiaFaculty of Computer Science and Information Technology, Gunadarma University, Jakarta, IndonesiaElectrical and Electronic Engineering Department, Centre for Intelligent Signal and Imaging Research, University Technology Petronas, Seri Iskandar, MalaysiaElectrical and Electronic Engineering Department, Centre for Intelligent Signal and Imaging Research, University Technology Petronas, Seri Iskandar, MalaysiaPolarization imaging can be used to improve the image quality by reducing the effects of the unwanted light reflection, enhancing the quality of images taken in non-ideal conditions, such as foggy weather, or reconstructing the 3D form of an object based on the shape from polarization. Reconstructing a 3D form requires the acquisition of multiple images and inference of the polarization parameters, such as the degree of polarization and angle of polarization, from these experimental data. The light polarization extraction process should begin by performing the photometric calibration to improve the performance of the polarize instrument measurements by reducing the measurement errors and improving the consistency between measurements. We propose an algorithm based on the kernel ridge regression method to estimate both the polarization parameters and the measurement (angle) errors in the placement of the polarizer. The algorithm was tested on four different sets of images containing different objects based on their responses to light and polarization. The algorithm that uses the mixed kernel function gives the best results.https://ieeexplore.ieee.org/document/8648346/Calibrationkernel ridge regressionpolarizationpolarizer |
| spellingShingle | Eri Prasetyo Wibowo Aini Suri Talita Mohammad Iqbal Achmad Benny Mutiara Cheng-Kai Lu Fabrice Meriaudeau An Improved Calibration Technique for Polarization Images IEEE Access Calibration kernel ridge regression polarization polarizer |
| title | An Improved Calibration Technique for Polarization Images |
| title_full | An Improved Calibration Technique for Polarization Images |
| title_fullStr | An Improved Calibration Technique for Polarization Images |
| title_full_unstemmed | An Improved Calibration Technique for Polarization Images |
| title_short | An Improved Calibration Technique for Polarization Images |
| title_sort | improved calibration technique for polarization images |
| topic | Calibration kernel ridge regression polarization polarizer |
| url | https://ieeexplore.ieee.org/document/8648346/ |
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