Image

Résumé

Une image est une représentation visuelle, voire mentale, de quelque chose (objet, être vivant ou concept). Elle peut être naturelle (ombre, reflet) ou artificielle (sculpture, peinture, photographie), visuelle ou non, tangible ou conceptuelle (métaphore), elle peut entretenir un rapport de ressemblance directe avec son modèle ou au contraire y être liée par un rapport plus symbolique. Pour la sémiologie ou sémiotique, qui a développé tout un secteur de sémiotique visuelle, l'image est conçue comme produite par un langage spécifique. Platon donne une des plus anciennes définitions de l'image : Le mot image en français vient du latin imago, qui désignait autrefois les masques mortuaires. Qu'est ce qu'une image ? . L’image se définirait comme une représentation ou une reproduction de quelque chose. Elle vient du latin « imago » qui désignait une sorte de masque moulé, à partir de cire d'abeille, sur le visage d’une personne morte afin d'en conserver les traits, com

Source officielle

https://fr.wikipedia.org/wiki/Image

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High sensitivity, incoherent differential imaging

Chiara Bonati

Microscopic visualisation of optically transparent samples has been a topic of interest for several decades. Features such as density or chemical composition can influence the optical phase of transmitted light, and phase contrast can reveal these structures. Several methods of phase contrast have been developed, which can be categorised as either interferometric or non-interferometric, based on the type of coherence properties of the light used. In this work, I focus on incoherent based phase contrast, in particular Differential Phase Contrast (DPC). The choice of incoherent light brings benefits such as the absence of distortions like speckle patterns and ringing patterns, increased spatial resolution, and a simpler setup that can be used for in-vivo applications. Moreover, DPC allows reconstruction of quantitative phase maps of the samples. On the other hand, coherent-based techniques demonstrate superior performance in terms of phase sensitivity. The first part of this thesis offers a quantitative analysis of the phase sensitivity of DPC and investigates the influence of optical parameters and sample characteristics. With simulations and experiments, a relation between numerical aperture and phase sensitivity is demonstrated, and the concept of spectral matching is introduced to enhance the contrast. The methods can be generalised to any DPC setup, and allow a-priori investigation of the sensitivity of a DPC microscope at the design stage rather than through testing. Comparison between the best sensitivity that can be achieved in DPC and state-of-the-art interferometric techniques, shows that it is not possible to reach comparable single-shot performances. In this thesis, it is shown that the reason for this limitation is the strong background in DPC images, which degrades the dynamic range. DPC images are obtained with mirrored illuminations, for which the background is identical and the phase term switches in sign. The difference between these pairs of images is computed digitally, which does not improve the limited dynamic range. Lock-in DPC is proposed as a solution: instead of sampling different illumination states, lock-in DPC demodulates the phase signal when the illumination is switched, and the background is never encoded. This is enabled by periodical switching of sources coupled with a smart pixel detector, the so-called "lock-in camera". Part of this work is dedicated to the theoretical description of this method, and the analysis of the expected benefit. Experiments are also described, that demonstrate a factor of 8 improvement in single-shot sensitivity compared to standard DPC. DPC is not the only imaging technique to suffer from high intensity background: it is easy to see how the use of a lock-in camera for differential imaging can be generalised to any situation where weak modulations can be induced over a strong background. Here, an example is presented with lock-in Shifted Excitation Raman Difference Spectroscopy (SERDS). SERDS is an established Raman spectroscopy technique that takes advantage of the Raman emission spectrum being relative to the excitation wavelength to remove unwanted fluorescence emission. Two spectra with shifted excitation wavelengths are measured, their difference is computed, and the fluorescence is thus digitally removed. The parallel with DPC is immediately apparent. Both simulations and experiments are used to demonstrate the advantage of analog demodulation.

EPFL2022

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Determining the relationship between the cause of damage and the subsequent structural behavior of infrastructure systems requires an accurate characterization of the propagation of cracks, which represents the evolution of the damage state. When no information about the cause of damage is available, kinematic approaches can be used to describe the motion of crack contours. Current image-based approaches to derive crack kinematics use digital image correlation (DIC) on a set of sequential images as the crack propagates. However, DIC is invasive in that the structure surfaces must be painted with random speckle patterns, limiting its use primarily to controlled experiments. In this paper, we propose a novel image-based methodology for computing crack opening in Mode I or Mode II. As an input, this method takes a binary image from a semantic segmentation of an image of a crack pattern. This binary image is used to detect the opposite edges along the crack, which are then registered using an optimization algorithm based on the Euclidean transformation model and non-linear least squares. As a final output, this method produces displacement maps in the tangential and normal directions to the crack skeleton. To demonstrate its performance, we validate our methodology first with synthetic crack patterns and then with real crack patterns. Because this methodology for determining crack openings requires only simple data (just a binary crack pattern image), it is straightforward, robust, and adaptable, thus contributing to the development of structural image-based damage assessments. The computational codes and datasets are available to the public for future research and benchmarking on https://github.com/eesd-epfl/crack_kinematics and https://doi.org/10.5281/zenodo.6632071.

ELSEVIER SCI LTD2022

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Generative Adversarial Network (GAN) based localized image editing can suffer from ambiguity between semantic attributes. We thus present a novel objective function to evaluate the locality of an image edit. By introducing the supervision from a pre-trained segmentation network and optimizing the objective function, our framework, called Locally Effective Latent Space Direction (LELSD), is applicable to any dataset and GAN architecture. Our method is also computationally fast and exhibits a high extent of disentanglement, which allows users to interactively perform a sequence of edits on an image. Our experiments on both GAN-generated and real images qualitatively demonstrate the high quality and advantages of our method.

IEEE2021

Chargement

High sensitivity, incoherent differential imaging

Chiara Bonati

EPFL2022