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16th Congress of the International Commission for Optics: Optics as a Key to High Technology

Modulation instability in the fiber doped with two-level atoms

Sien Chi

Published Jul 23, 1993• 0 citations
Publisher

Abstract

The retinal image quality in the human eye have been measured by using a hybrid optical digital method, consisting in the recording and processing of retinal images of a point test after reflection in the retina. The method allows one to obtain accurate data on the modulation transfer function of the eye, which can be directly used in vision research and practical optical engineering studies. The technique has been used to obtain image quality results both in the fovea and the periphery under different experimental conditions. These results have some implications to retinal sampling: in natural viewing the eye's optics provides a good protection against aliasing (spatial undersampling) in the fovea, but leaving the cone mosaic least protected at eccentricities around 10 to 20 degrees. Experimental systems based on this optical digital technique might have potential applications to obtain high resolution fundus images in the living eye.

DOI
10.1117/12.2308787

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The retinal image quality in the human eye have been measured by using a hybrid optical digital method, consisting in the recording and processing of retinal images of a point test after reflection in the retina. The method allows one to obtain accurate data on the modulation transfer function of the eye, which can be directly used in vision research and practical optical engineering studies. The technique has been used to obtain image quality results both in the fovea and the periphery under different experimental conditions. These results have some implications to retinal sampling: in natural viewing the eye's optics provides a good protection against aliasing (spatial undersampling) in the fovea, but leaving the cone mosaic least protected at eccentricities around 10 to 20 degrees. Experimental systems based on this optical digital technique might have potential applications to obtain high resolution fundus images in the living eye.
This paper describes a computational approach to the theoretical problems involved in the Young's single-photon double-slit experiment, focusing on a simulation of this experiment in the absence of measuring devices. Specifically, the human visual system is used in place of a photomultiplier or similar apparatus. Beginning with the assumption that the human eye perceives light in the presence of very few photons, we measure human eye performance as a sensor in a double-slit one-photon-at-a-time experimental setup. To interpret the results, we implement a simulation algorithm and compare its results with those of human subjects under identical experimental conditions. In order to evaluate the perceptive parameters exactly, which vary depending on the light conditions and on the subject's sensitivity, we first review the existing literature on the biophysics of the human eye in the presence of a dim light source, and then use the known values of the experimental variables to set the parameters of the computational simulation. The results of the simulation and their comparison with the experiment involving human subjects are reported and discussed. It is found that, while the computer simulation indicates that the human eye has the capacity to detect the corpuscular nature of photons under these conditions, this was not observed in practice. The possible reasons for the difference between theoretical prediction and experimental results are discussed.
Generative learning models in medical research are crucial in developing training data for deep learning models and advancing diagnostic tools, but the problem of high quality, diverse images is an open topic of research. Quantum-enhanced generative models have been proposed and tested in the literature but have been restricted to small problems below the scale of industry relevance. In this paper, we propose quantum-enhanced diffusion and variational autoencoder (VAE) models and test them on the Fundus retinal image generation task. In our numerical experiments, the images generated using quantum-enhanced models are of higher quality and match more closely in features to the real image distribution compared to the ones generated using classical diffusion models, even when the classical diffusion models are larger than the quantum model. Additionally, we perform noisy testing and experimental runs on hardware to confirm the numerical experiments, finding that quantum-enhanced diffusion model can sometimes produce higher quality images, both in terms of diversity and fidelity, when tested with quantum noise.
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In human eyes, retina cells have shown complicated, sophisticated structures, and thus capability of carrying out certain basic visual functions. In computer vision, a spherical model has been proposed to demonstrate that certain basic visual functions can be performed at the sensor/photoreceptor level for target recognition, mobile robotic control, and other applications. This paper will establish that low level computer vision in this spherical model exhibits a Hamiltonian model of quantum computation. This results will be important to the understanding of human vision as well as the development of intelligent visual sensor chips and devices in electronics and optics.