The real-time positioning of an object on a microscopic scale is a significant challenge and remains difficult to apply. Many traditional imaging techniques exist but their axial resolution and/or their measurement range is often limited. We develop a novel high‐profile technology based on three pillars to meet these challenges. Using digital holography, we determine the correct focus distance on a large scale. Secondly, a new generation transformer neural networks processes the hologram giving in real-time (~30 frames per seconds) a submicrometric axial resolution, exceeding therefore the diffraction limit of the depth of field. Finally, the spatial structuring of the object allows us a nanometric lateral positioning by classical techniques, which will be sped up by a machine learning technique. Such high frame rates enable real-time processing in many different application scenarios.
We develop a novel high‐profile application of machine learning techniques by elevating digital holography and sensing in robotics to a new level. The extraction of unknown metrics such as focusing distance and in plane positioning without full image restoration from digital holograms is performed by pre‐processing approach in space‐domain and/or in Fourier‐domain, including real‐time constraints. Measuring a single hologram, we successfully determine the axial distance of a complex object to the 10x microscope objective over a range of 100 µm with an accuracy of 1.25 µm. We apply a machine learning technique to the hologram to speed up tracking in the plane of the pseudo-periodic target position up to several tens of frames per second (fps). Such high frame rates enable real-time processing in many different application scenarios.
Reversible switching of physical and chemical properties can be achieved by light, by means of photochromic substances. A large number of applications are sought for: protection against light, hyper-resolution microscopy, memories, etc. Moreover, photochromic molecules or moieties can be associated to other molecules or moieties with high performance in a given property for the purpose of switching. For example, materials containing photochromic and fluorescent molecules or moieties, interacting at a nanometric scale, are being investigated, for fluorescence photoswitching between OFF (no emission of light) and ON (with emission of light) states.
A general concern is to obtain big effects with small inputs. In this regard, our strategy is based on the exploitation of nanoscale interactions, such as energy transfer or plasmonic effect, in order to amplify photoswitching. In our presentation, we will focus on two aspects:
1. Accelerated photoswitching, in hybrid systems, containing gold nanoparticles and photochromic molecules. Due to plasmonic effect taking place in the gold nanoparticles, an increase of the photoswitching rate of the photochromic molecules is observed.
2. Enhanced photoswitching of fluorescence in nanoparticles containing photochromic and fluorescent moieties. The fluorescence of a large number (up to 400 moieties) can be turned ON or OFF by only one photon. This unconventional phenomenon was obserd in various systems: multichromophoric molecules, nanoparticles containing photochrome-fluorophore dyads, and silica nanoparticles grafted with photochromic and fluorescent moieties. This effect stems from the multiple energy transfer occurring at molecular and nanometric scale.
We propose a vision-based position sensor based on Digital Holography (DH) for in-plane and out-of-plane displacements measurement of a patterned plate with sub-pixel resolutions. DH is a lensless imaging principle using solid-state camera and/or spatial light modulators (SLM). Object scenes are generated or reconstructed numerically through wave propagation computations applied to a diffracted optical field recorded as an interferogram. The application of visual positioning to manipulation tasks in micro-robotics requires high accuracy and wide ranges of displacements that, unfortunately, are limited by finite depth-of-focus and fixed working distance of refractive imaging systems. Recently, we demonstrated that DH allows in-plane positioning of mobile targets ensuring nanometer resolutions at diverse working distances within a continuous range of more than 15 centimeters. By recording a set of digital holograms of a pseudo-periodic pattern fixed onto a moving target, images in phase and in intensity are restored by numerical reconstruction using Angular Spectrum Propagation methods by adjusting the reconstruction distance. A last step consists in performing a direct phase measurements of periodic pattern to reach nanometer resolutions. Three 2DFFT are required at minimum to extract the pattern position, which is time consuming if several hundred of holograms are recorded. We explore a new approach that consists to restore in-plane / out-of-plane position directly from the 2DFFT of the digital hologram without any need for image restitution. The proposed vision-based position sensor combines a 10 Mp CMOS camera and a SLM in order to perform a fine control of the interferometer reference arm.
In order to increase Signal to Noise Ratio of very high resolution Earth observation satellites images, Time Delay Integration (TDI) sensors are usually used. A TDI device synchronizes the electronic charge transfer with the satellite speed to virtually increase exposure time and thus signal to noise ratio. It is sensitive to high frequency attitude disturbances which may induce blurring effects when increasing time exposure. In this paper, we present an on-board satellite implementation of multiframe registration to improve classical TDI performances. A solution to no longer constrain the number of lines to be accumulated would be to compute, in real-time, the shift between each line and resample them before summation. A motion sensor dedicated to shift measurements would be added in the focal plane. Then a fast real-time algorithm will compute shift between two consecutives images delivered by the motion sensor. The optimization study of the motion sensor and the performances of a gradient-based algorithm on these images will be presented.
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