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Generalized image deconvolution by exploiting the transmission matrix of an optical imaging system
- Source :
- Scientific Reports, Vol 7, Iss 1, Pp 1-10 (2017), Scientific Reports, SCIENTIFIC REPORTS(7)
- Publication Year :
- 2017
- Publisher :
- Nature Portfolio, 2017.
-
Abstract
- Intact optical information of an object delivered through an imaging system is deteriorated by imperfect optical elements and unwanted defects. Image deconvolution has been widely exploited as a recovery technique due to its practical feasibility, and operates by assuming linear shift-invariant property of the imaging system. However, shift invariance does not rigorously hold in all imaging situations and is not a necessary condition for solving an inverse problem of light propagation. Several improved deconvolution techniques exploiting spatially variant point spread functions have been proposed in previous studies. However, the full characterization of an optical imaging system for compensating aberrations has not been considered. Here, we present a generalized method to solve the linear inverse problem of coherent light propagations without any regularization method or constraint on shift invariance by fully measuring the transmission matrix of the imaging system. Our results show that severe aberrations produced by a tilted lens or an inserted disordered layer can be corrected properly only by the proposed generalized image deconvolution. This work generalizes the theory of image deconvolution, and enables distortion-free imaging under general imaging condition.
- Subjects :
- Blind deconvolution
Point spread function
Computer science
Science
Transmission matrix
02 engineering and technology
01 natural sciences
Article
010309 optics
0103 physical sciences
Computer vision
Adaptive optics
Multidisciplinary
business.industry
Inverse problem
021001 nanoscience & nanotechnology
Regularization (physics)
Medicine
Artificial intelligence
Deconvolution
Tomography
0210 nano-technology
business
Algorithm
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 7
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....67acaba324baa0578d220b8991f192f7