A new polarization image demosaicking algorithm by exploiting inter-channel correlations with guided filtering
This paper presents a fast and effective polarization image demosaicking algorithm, which explores inter-channel dependency of Stokes parameters for the minimization of residual aliasing artifacts after cubic spline interpolation. A guided filtering approach is used for denoising. An optimization ba...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
2021
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| Online Access: | https://hdl.handle.net/10356/145824 |
| _version_ | 1811683743233998848 |
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| author | Liu, Shumin Chen, Jiajia Xun, Yuan Zhao, Xiaojin Chang, Chip-Hong |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Liu, Shumin Chen, Jiajia Xun, Yuan Zhao, Xiaojin Chang, Chip-Hong |
| author_sort | Liu, Shumin |
| collection | NTU |
| description | This paper presents a fast and effective polarization image demosaicking algorithm, which explores inter-channel dependency of Stokes parameters for the minimization of residual aliasing artifacts after cubic spline interpolation. A guided filtering approach is used for denoising. An optimization based on the confidence level of the aforementioned guided filtering, the correlations between the demosaicked image and input, as well as the total intensity, angle and degree of linear polarization, is constructed and solved with Newton’s method. Experimental results demonstrate that the proposed algorithm can surpass the existing methods in terms of both objective root mean squared error and structural similarity index by at least 36.0% and 3.4%, respectively, and by close visual inspection of the clarity of objects in the angle and degree of linear polarization images. The proposed algorithm consists of only convolutions and elementwise operations, making it fast and parallelizable for efficient GPU acceleration. An image of size 512×612×4 can be processed within 10 s on i7-6700k CPU, and gains further 5 times speedup with M4000M GPU. |
| first_indexed | 2024-10-01T04:17:35Z |
| format | Journal Article |
| id | ntu-10356/145824 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:17:35Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1458242021-01-11T02:05:08Z A new polarization image demosaicking algorithm by exploiting inter-channel correlations with guided filtering Liu, Shumin Chen, Jiajia Xun, Yuan Zhao, Xiaojin Chang, Chip-Hong School of Electrical and Electronic Engineering Centre for Integrated Circuits and Systems Engineering::Electrical and electronic engineering Guided Filter Image Demosaicking This paper presents a fast and effective polarization image demosaicking algorithm, which explores inter-channel dependency of Stokes parameters for the minimization of residual aliasing artifacts after cubic spline interpolation. A guided filtering approach is used for denoising. An optimization based on the confidence level of the aforementioned guided filtering, the correlations between the demosaicked image and input, as well as the total intensity, angle and degree of linear polarization, is constructed and solved with Newton’s method. Experimental results demonstrate that the proposed algorithm can surpass the existing methods in terms of both objective root mean squared error and structural similarity index by at least 36.0% and 3.4%, respectively, and by close visual inspection of the clarity of objects in the angle and degree of linear polarization images. The proposed algorithm consists of only convolutions and elementwise operations, making it fast and parallelizable for efficient GPU acceleration. An image of size 512×612×4 can be processed within 10 s on i7-6700k CPU, and gains further 5 times speedup with M4000M GPU. Ministry of Education (MOE) Accepted version This work was supported in part by the Nanjing University of Aeronautics and Astronautics, Nanjing, China, under Grant 56Y AH18043 and Grant PAC19009 and in part by the Singapore Ministry of Education AcRF Tier 1 under Grant MOE2018-T1- 001-131, RG87/18-(S). 2021-01-11T02:05:08Z 2021-01-11T02:05:08Z 2020 Journal Article Liu, S., Chen, J., Xun, Y., Zhao, X., & Chang, C.-H. (2020). A new polarization image demosaicking algorithm by exploiting inter-channel correlations with guided filtering. IEEE Transactions on Image Processing, 29, 7076-7089. doi:10.1109/TIP.2020.2998281 1941-0042 https://hdl.handle.net/10356/145824 10.1109/TIP.2020.2998281 29 7076 7089 en MOE2018-T1- 001-131, RG87/18-(S) IEEE Transactions on Image Processing © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TIP.2020.2998281 application/pdf |
| spellingShingle | Engineering::Electrical and electronic engineering Guided Filter Image Demosaicking Liu, Shumin Chen, Jiajia Xun, Yuan Zhao, Xiaojin Chang, Chip-Hong A new polarization image demosaicking algorithm by exploiting inter-channel correlations with guided filtering |
| title | A new polarization image demosaicking algorithm by exploiting inter-channel correlations with guided filtering |
| title_full | A new polarization image demosaicking algorithm by exploiting inter-channel correlations with guided filtering |
| title_fullStr | A new polarization image demosaicking algorithm by exploiting inter-channel correlations with guided filtering |
| title_full_unstemmed | A new polarization image demosaicking algorithm by exploiting inter-channel correlations with guided filtering |
| title_short | A new polarization image demosaicking algorithm by exploiting inter-channel correlations with guided filtering |
| title_sort | new polarization image demosaicking algorithm by exploiting inter channel correlations with guided filtering |
| topic | Engineering::Electrical and electronic engineering Guided Filter Image Demosaicking |
| url | https://hdl.handle.net/10356/145824 |
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