Polarimetric Image Discrimination With Depolarization Mueller Matrix
Polarimetric imaging techniques exploit the polarization characteristics of objects and, thus, can achieve a better discriminative performance. In this paper, an adaptive discrimination method based on the classification of depolarization Mueller matrix is proposed. According to the Mueller ...
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| Format: | Article |
| Language: | English |
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IEEE
2016-01-01
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| Series: | IEEE Photonics Journal |
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| Online Access: | https://ieeexplore.ieee.org/document/7752873/ |
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| author | Pengcheng Wang Qian Chen Guohua Gu Weixian Qian Kan Ren |
| author_facet | Pengcheng Wang Qian Chen Guohua Gu Weixian Qian Kan Ren |
| author_sort | Pengcheng Wang |
| collection | DOAJ |
| description | Polarimetric imaging techniques exploit the polarization characteristics of objects and, thus, can achieve a better discriminative performance. In this paper, an adaptive discrimination method based on the classification of depolarization Mueller matrix is proposed. According to the Mueller–Jones theory, the general formula of Mueller matrix for depolarization optical system is analyzed. In addition, a two-channel imaging platform is constructed to obtain a polarization-difference image with certain states of polarization. Under this methodology, every pixel of the image can be expanded as a combination of independent entries of the Mueller matrix, with polarization states as the representative coefficients. Thus, the optimal polarization states can be obtained via support vector machine (SVM), and a high contrast image is achieved. Finally, experiments on two groups of different materials are conducted to demonstrate the applicability and performance of the proposed method. The related criteria (e.g., Fisher ratio) are introduced to quantitatively evaluate the results. Experimental results indicate that the proposed method shows advantages for image discriminations. |
| format | Article |
| id | doaj-art-3e7ea84942e94d9b9e54bd31c16fbfb5 |
| institution | Matheson Library |
| issn | 1943-0655 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj-art-3e7ea84942e94d9b9e54bd31c16fbfb52025-07-01T23:16:17ZengIEEEIEEE Photonics Journal1943-06552016-01-018611310.1109/JPHOT.2016.26308437752873Polarimetric Image Discrimination With Depolarization Mueller MatrixPengcheng Wang0Qian Chen1Guohua Gu2Weixian Qian3Kan Ren4Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, ChinaJiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, ChinaJiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, ChinaJiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, ChinaJiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, ChinaPolarimetric imaging techniques exploit the polarization characteristics of objects and, thus, can achieve a better discriminative performance. In this paper, an adaptive discrimination method based on the classification of depolarization Mueller matrix is proposed. According to the Mueller–Jones theory, the general formula of Mueller matrix for depolarization optical system is analyzed. In addition, a two-channel imaging platform is constructed to obtain a polarization-difference image with certain states of polarization. Under this methodology, every pixel of the image can be expanded as a combination of independent entries of the Mueller matrix, with polarization states as the representative coefficients. Thus, the optimal polarization states can be obtained via support vector machine (SVM), and a high contrast image is achieved. Finally, experiments on two groups of different materials are conducted to demonstrate the applicability and performance of the proposed method. The related criteria (e.g., Fisher ratio) are introduced to quantitatively evaluate the results. Experimental results indicate that the proposed method shows advantages for image discriminations.https://ieeexplore.ieee.org/document/7752873/Polarimetric imagingMueller matrixcontrast enhancementpattern classification |
| spellingShingle | Pengcheng Wang Qian Chen Guohua Gu Weixian Qian Kan Ren Polarimetric Image Discrimination With Depolarization Mueller Matrix IEEE Photonics Journal Polarimetric imaging Mueller matrix contrast enhancement pattern classification |
| title | Polarimetric Image Discrimination With Depolarization Mueller Matrix |
| title_full | Polarimetric Image Discrimination With Depolarization Mueller Matrix |
| title_fullStr | Polarimetric Image Discrimination With Depolarization Mueller Matrix |
| title_full_unstemmed | Polarimetric Image Discrimination With Depolarization Mueller Matrix |
| title_short | Polarimetric Image Discrimination With Depolarization Mueller Matrix |
| title_sort | polarimetric image discrimination with depolarization mueller matrix |
| topic | Polarimetric imaging Mueller matrix contrast enhancement pattern classification |
| url | https://ieeexplore.ieee.org/document/7752873/ |
| work_keys_str_mv | AT pengchengwang polarimetricimagediscriminationwithdepolarizationmuellermatrix AT qianchen polarimetricimagediscriminationwithdepolarizationmuellermatrix AT guohuagu polarimetricimagediscriminationwithdepolarizationmuellermatrix AT weixianqian polarimetricimagediscriminationwithdepolarizationmuellermatrix AT kanren polarimetricimagediscriminationwithdepolarizationmuellermatrix |