Transmission of natural scene images through a multimode fibre

The optical transport of images through a multimode fibre remains an outstanding challenge with applications ranging from optical communications to neuro-imaging. State of the art approaches either involve measurement and control of the full complex field transmitted through the fibre or, more recently, training of artificial neural networks that however, are typically limited to image classes belong to the same class as the training data set. Here we implement a method that statistically reconstructs the inverse transformation matrix for the fibre. We demonstrate imaging at high frame rates, high resolutions and in full colour of natural scenes, thus demonstrating general-purpose imaging capability. Real-time imaging over long fibre lengths opens alternative routes to exploitation for example for secure communication systems, novel remote imaging devices, quantum state control processing and endoscopy

Deep, Complex, Invertible Networks for Inversion of Transmission Effects in Multimode Optical Fibres

We use complex-weighted, deep networks to invert the effects of multimode optical fibre distortion of a coherent input image. We generated experimental data based on collections of optical fibre responses to greyscale input images generated with coherent light, by measuring only image amplitude (not amplitude and phase as is typical) at the output of \SI{1}{\metre} and \SI{10}{\metre} long, \SI{105}{\micro\metre} diameter multimode fibre. This data is made available as the {\it Optical fibre inverse problem} Benchmark collection. The experimental data is used to train complex-weighted models with a range of regularisation approaches. A {\it unitary regularisation} approach for complex-weighted networks is proposed which performs well in robustly inverting the fibre transmission matrix, which fits well with the physical theory. A key benefit of the unitary constraint is that it allows us to learn a forward unitary model and analytically invert it to solve the inverse problem. We demonstrate this approach, and show how it can improve performance by incorporating knowledge of the phase shift induced by the spatial light modulator

Deep, Complex, Invertible Networks for Inversion of Transmission Effects in Multimode Optical Fibres

We use complex-weighted, deep networks to invert the effects of multimode optical fibre distortion of a coherent input image. We generated experimental data based on collections of optical fibre responses to greyscale input images generated with coherent light, by measuring only image amplitude (not amplitude and phase as is typical) at the output of \SI{1}{\metre} and \SI{10}{\metre} long, \SI{105}{\micro\metre} diameter multimode fibre. This data is made available as the {\it Optical fibre inverse problem} Benchmark collection. The experimental data is used to train complex-weighted models with a range of regularisation approaches. A {\it unitary regularisation} approach for complex-weighted networks is proposed which performs well in robustly inverting the fibre transmission matrix, which fits well with the physical theory. A key benefit of the unitary constraint is that it allows us to learn a forward unitary model and analytically invert it to solve the inverse problem. We demonstrate this approach, and show how it can improve performance by incorporating knowledge of the phase shift induced by the spatial light modulator

The value of plantation forests for plant, invertebrate and bird diversity and the potential for cross-taxon surrogacy

As the area of plantation forest expands worldwide and natural, unmanaged forests decline there is much interest in the potential for planted forests to provide habitat for biodiversity. In regions where little semi-natural woodland remains, the biodiversity supported by forest plantations, typically non-native conifers, may be particularly important. Few studies provide detailed comparisons between the species diversity of native woodlands which are being depleted and non-native plantation forests, which are now expanding, based on data collected from multiple taxa in the same study sites. Here we compare the species diversity and community composition of plants, invertebrates and birds in Sitka spruce- (Picea sitchensis-) dominated and Norway spruce- (Picea abies-) dominated plantations, which have expanded significantly in recent decades in the study area in Ireland, with that of oak- and ash-dominated semi-natural woodlands in the same area. The results show that species richness in spruce plantations can be as high as semi-natural woodlands, but that the two forest types support different assemblages of species. In areas where non-native conifer plantations are the principle forest type, their role in the provision of habitat for biodiversity conservation should not be overlooked. Appropriate management should target the introduction of semi-natural woodland characteristics, and on the extension of existing semi-natural woodlands to maintain and enhance forest species diversity. Our data show that although some relatively easily surveyed groups, such as vascular plants and birds, were congruent with many of the other taxa when looking across all study sites, the similarities in response were not strong enough to warrant use of these taxa as surrogates of the others. In order to capture a wide range of biotic variation, assessments of forest biodiversity should either encompass several taxonomic groups, or rely on the use of indicators of diversity that are not species based

Imaging natural scenes with a multi-mode a fibre

Data for the paper 'Imaging natural scenes with a multi-mode a fibre'