Efficient Gaussian inference algorithms for phase imaging
Novel efficient algorithms are developed to infer the phase of a complex optical field from a sequence of intensity images taken at different defocus distances. The non-linear observation model is approximated by a linear model. The complex optical field is inferred by iterative Kalman smoothing in...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/98783 http://hdl.handle.net/10220/13405 |
| _version_ | 1811692835554983936 |
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| author | Vazquez, Manuel A. Zhong, Jingshan Dauwels, Justin Waller, Laura |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Vazquez, Manuel A. Zhong, Jingshan Dauwels, Justin Waller, Laura |
| author_sort | Vazquez, Manuel A. |
| collection | NTU |
| description | Novel efficient algorithms are developed to infer the phase of a complex optical field from a sequence of intensity images taken at different defocus distances. The non-linear observation model is approximated by a linear model. The complex optical field is inferred by iterative Kalman smoothing in the Fourier domain: forward and backward sweeps of Kalman recursions are alternated, and in each such sweep, the approximate linear model is refined. By limiting the number of iterations, one can trade off accuracy vs. complexity. The complexity of each iteration in the proposed algorithm is in the order of N logN, where N is the number of pixels per image. The storage required scales linearly with N. In contrast, the complexity of existing phase inference algorithms scales with N3 and the required storage with N2. The proposed algorithms may enable real-time estimation of optical fields from noisy intensity images. |
| first_indexed | 2024-10-01T06:42:06Z |
| format | Conference Paper |
| id | ntu-10356/98783 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:42:06Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/987832020-03-07T13:24:48Z Efficient Gaussian inference algorithms for phase imaging Vazquez, Manuel A. Zhong, Jingshan Dauwels, Justin Waller, Laura School of Electrical and Electronic Engineering IEEE International Conference on Acoustics, Speech and Signal Processing (2012 : Kyoto, Japan) DRNTU::Engineering::Electrical and electronic engineering Novel efficient algorithms are developed to infer the phase of a complex optical field from a sequence of intensity images taken at different defocus distances. The non-linear observation model is approximated by a linear model. The complex optical field is inferred by iterative Kalman smoothing in the Fourier domain: forward and backward sweeps of Kalman recursions are alternated, and in each such sweep, the approximate linear model is refined. By limiting the number of iterations, one can trade off accuracy vs. complexity. The complexity of each iteration in the proposed algorithm is in the order of N logN, where N is the number of pixels per image. The storage required scales linearly with N. In contrast, the complexity of existing phase inference algorithms scales with N3 and the required storage with N2. The proposed algorithms may enable real-time estimation of optical fields from noisy intensity images. 2013-09-09T07:14:54Z 2019-12-06T19:59:37Z 2013-09-09T07:14:54Z 2019-12-06T19:59:37Z 2012 2012 Conference Paper https://hdl.handle.net/10356/98783 http://hdl.handle.net/10220/13405 10.1109/ICASSP.2012.6287959 en |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Vazquez, Manuel A. Zhong, Jingshan Dauwels, Justin Waller, Laura Efficient Gaussian inference algorithms for phase imaging |
| title | Efficient Gaussian inference algorithms for phase imaging |
| title_full | Efficient Gaussian inference algorithms for phase imaging |
| title_fullStr | Efficient Gaussian inference algorithms for phase imaging |
| title_full_unstemmed | Efficient Gaussian inference algorithms for phase imaging |
| title_short | Efficient Gaussian inference algorithms for phase imaging |
| title_sort | efficient gaussian inference algorithms for phase imaging |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/98783 http://hdl.handle.net/10220/13405 |
| work_keys_str_mv | AT vazquezmanuela efficientgaussianinferencealgorithmsforphaseimaging AT zhongjingshan efficientgaussianinferencealgorithmsforphaseimaging AT dauwelsjustin efficientgaussianinferencealgorithmsforphaseimaging AT wallerlaura efficientgaussianinferencealgorithmsforphaseimaging |