Experimental far-field imaging properties of high refractive index microsphere lens

The far-field imaging properties of a high index microsphere lens spatially separated from the object are experimentally studied. Our experimental results show that, for a Blu-ray disk whose spacing is 300 nm, the high index microsphere lens also can discern the patterns of the object sample when the distance between the lens and the object is up to 5.4 μm. When the distance is increased from 0 to 5.4 μm, for the microsphere lens with a diameter of 24 μm, the lateral magnification increases from 3.5× to 5.5×, while the field of view decreases from 5.1 to 3.0 μm. By varying the distance between the lens and the object, the optical image can be optimized. We also indicate that the far-field imaging capability of a high index microsphere lens is dependent on the electromagnetic field intensityprofile of the photonic nanojet under different positions of the microsphere lens.

Imaging Properties of Planar Microlens Arrays

The planar microlens arrays is a two-dimensional array of optical component which is fabricated monolithically available. Imaging properties of planar microlens arrays are described, which provide both image multiplexer and erect, unit magnification images.

Asymmetric Loss Based on Image Properties for Deep Learning-Based Image Restoration

Deep learning techniques have significantly improved image restoration tasks in recent years.As a crucial compo-nent of deep learning,the loss function plays a key role in network optimization and performance enhancement.However,the currently prevalent loss functions assign equal weight to each pixel point during loss calculation,which hampers the ability to reflect the roles of different pixel points and fails to exploit the image’s characteristics fully.To address this issue,this study proposes an asymmetric loss function based on the image and data characteristics of the image recovery task.This novel loss function can adjust the weight of the reconstruction loss based on the grey value of different pixel points,thereby effectively optimizing the network training by differentially utilizing the grey information from the original image.Specifically,we calculate a weight factor for each pixel point based on its grey value and combine it with the reconstruction loss to create a new loss function.This ensures that pixel points with smaller grey values receive greater attention,improving network recovery.In order to verify the effectiveness of the proposed asymmetric loss function,we conducted experimental tests in the image super-resolution task.The experimental results show that the model with the introduction of asymmetric loss weights improves all the indexes of the processing results without increasing the training time.In the typical super-resolution network SRCNN,by introducing asymmetric weights,it is possible to improve the peak signal-to-noise ratio(PSNR)by up to about 0.5%,the structural similarity index(SSIM)by up to about 0.3%,and reduce the root-mean-square error(RMSE)by up to about 1.7%with essentially no increase in training time.In addition,we also further tested the performance of the proposed method in the denoising task to verify the potential applicability of the method in the image restoration task.

Optimizing signal collection efficiency of the VIPA-based Brillouin spectrometer

Brillouin spectroscopy is an emerging tool for microscopic optical imaging as it allows for non-invasive and direct assessment of the viscoelastic properties of materials.Recent advances of background-free confocal Brillouin spectrometer allows investigators to acquire the Brillouin spectra for turbid samples as well as transparent ones.However,due to strong signal loss induced by the imperfect optical setup,the Brillouin photons are usually immersed in background noise.In this report,we proposed and experimentally demonstrated multiple approaches to enhance the signal collction eficiency.A signal enhancement by>4 times can be observed,enabling ob-servation of ultra-weak signals.

The Image Property in an EIT Information Transfer System

We focus on the study of the transferred image property in an electromagnetically induced transparency （EIT）system. In our experiment, a triple-peak image is effectively transferred trom a coupling beam to a signal beam based on the FIT effect. It is found that the transferred image intensity profile of the signal beam is the same as that of the coupling beam while not in phase. Furthermore, the propagation property of the transferred image is studied. Due to the narrowing effect, the transferred image keeps narrowing and maintains the shape well within a certain distance outside of the medium. Our experimental results are in excellent agreement with the theoretical analysis.