scholarly journals Divide and conquer: real-time maximum likelihood fitting of multiple emitters for super-resolution localization microscopy

2019 ◽  
Vol 27 (15) ◽  
pp. 21029 ◽  
Author(s):  
Luchang Li ◽  
Bo Xin ◽  
Weibing Kuang ◽  
Zhiwei Zhou ◽  
Zhen-Li Huang
Keyword(s):  
Maximum Likelihood ◽  
Real Time ◽  
Super Resolution ◽  
Divide And Conquer ◽  
Localization Microscopy

scholarly journals Divide and Conquer: Real-time maximum likelihood fitting of multiple emitters for super-resolution localization microscopy

2019 ◽  
Author(s):  
Luchang Li ◽  
Bo Xin ◽  
Weibing Kuang ◽  
Zhiwei Zhou ◽  
Zhen-Li Huang
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Super Resolution ◽  
Large Cell ◽  
Field Of View ◽  
Divide And Conquer ◽  
Image Size ◽  
Localization Microscopy ◽  
Localization Algorithms ◽  
Emitter Localization

AbstractMulti-emitter localization has great potential for maximizing the imaging speed of super-resolution localization microscopy. However, the slow image analysis speed of reported multi-emitter localization algorithms limits their usage in mostly off-line image processing with small image size. Here we adopt the well-known divide and conquer strategy in computer science and present a fitting-based method called QC-STORM for fast multi-emitter localization. Using simulated and experimental data, we verify that QC-STORM is capable of providing real-time full image processing on raw images with 100 µm × 100 µm field of view and 10 ms exposure time, with comparable spatial resolution as the popular fitting-based ThunderSTORM and the up-to-date non-iterative WindSTORM. This study pushes the development and practical use of super-resolution localization microscopy in high-throughput or high-content imaging of cell-to-cell differences or discovering rare events in a large cell population.

scholarly journals Real-time adaptive drift correction for super-resolution localization microscopy

2015 ◽  
Vol 23 (18) ◽  
pp. 23887 ◽  
Author(s):  
Ginni Grover ◽  
Wyatt Mohrman ◽  
Rafael Piestun
Keyword(s):  
Real Time ◽  
Super Resolution ◽  
Drift Correction ◽  
Localization Microscopy

A real-time atmospheric turbulence mitigation and super-resolution solution for infrared imaging systems

2012 ◽  
Author(s):  
Douglas R. Droege ◽  
Russell C. Hardie ◽  
Brian S. Allen ◽  
Alexander J. Dapore ◽  
Jon C. Blevins
Keyword(s):  
Real Time ◽  
Atmospheric Turbulence ◽  
Infrared Imaging ◽  
Super Resolution ◽  
Imaging Systems

scholarly journals Comparing Super-Resolution Microscopy Techniques to Analyze Chromosomes

2021 ◽  
Vol 22 (4) ◽  
pp. 1903
Author(s):  
Ivona Kubalová ◽  
Alžběta Němečková ◽  
Klaus Weisshart ◽  
Eva Hřibová ◽  
Veit Schubert
Keyword(s):  
Single Molecule ◽  
Imaging Techniques ◽  
Chromatin Condensation ◽  
Super Resolution ◽  
Stimulated Emission ◽  
Wide Field ◽  
Structured Illumination Microscopy ◽  
Metaphase Chromosomes ◽  
Localization Microscopy ◽  
Super Resolution Microscopy

The importance of fluorescence light microscopy for understanding cellular and sub-cellular structures and functions is undeniable. However, the resolution is limited by light diffraction (~200–250 nm laterally, ~500–700 nm axially). Meanwhile, super-resolution microscopy, such as structured illumination microscopy (SIM), is being applied more and more to overcome this restriction. Instead, super-resolution by stimulated emission depletion (STED) microscopy achieving a resolution of ~50 nm laterally and ~130 nm axially has not yet frequently been applied in plant cell research due to the required specific sample preparation and stable dye staining. Single-molecule localization microscopy (SMLM) including photoactivated localization microscopy (PALM) has not yet been widely used, although this nanoscopic technique allows even the detection of single molecules. In this study, we compared protein imaging within metaphase chromosomes of barley via conventional wide-field and confocal microscopy, and the sub-diffraction methods SIM, STED, and SMLM. The chromosomes were labeled by DAPI (4′,6-diamidino-2-phenylindol), a DNA-specific dye, and with antibodies against topoisomerase IIα (Topo II), a protein important for correct chromatin condensation. Compared to the diffraction-limited methods, the combination of the three different super-resolution imaging techniques delivered tremendous additional insights into the plant chromosome architecture through the achieved increased resolution.

scholarly journals Real-Time Environment Monitoring Using a Lightweight Image Super-Resolution Network

2021 ◽  
Vol 18 (11) ◽  
pp. 5890
Author(s):  
Qiang Yu ◽  
Feiqiang Liu ◽  
Long Xiao ◽  
Zitao Liu ◽  
Xiaomin Yang
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Super Resolution ◽  
Model Complexity ◽  
Practical Application ◽  
Single Image ◽  
Feature Maps ◽  
Benchmark Datasets ◽  
Image Super Resolution ◽  
Single Image Super Resolution

Deep-learning (DL)-based methods are of growing importance in the field of single image super-resolution (SISR). The practical application of these DL-based models is a remaining problem due to the requirement of heavy computation and huge storage resources. The powerful feature maps of hidden layers in convolutional neural networks (CNN) help the model learn useful information. However, there exists redundancy among feature maps, which can be further exploited. To address these issues, this paper proposes a lightweight efficient feature generating network (EFGN) for SISR by constructing the efficient feature generating block (EFGB). Specifically, the EFGB can conduct plain operations on the original features to produce more feature maps with parameters slightly increasing. With the help of these extra feature maps, the network can extract more useful information from low resolution (LR) images to reconstruct the desired high resolution (HR) images. Experiments conducted on the benchmark datasets demonstrate that the proposed EFGN can outperform other deep-learning based methods in most cases and possess relatively lower model complexity. Additionally, the running time measurement indicates the feasibility of real-time monitoring.

scholarly journals A Residual Network and FPGA Based Real-Time Depth Map Enhancement System

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 546
Author(s):  
Zhenni Li ◽  
Haoyi Sun ◽  
Yuliang Gao ◽  
Jiao Wang
Keyword(s):  
Real Time ◽  
Super Resolution ◽  
Depth Map ◽  
Acquisition System ◽  
Depth Image ◽  
Fpga Design ◽  
Depth Sensing ◽  
Residual Network ◽  
Real Time Processing ◽  
Depth Maps

Depth maps obtained through sensors are often unsatisfactory because of their low-resolution and noise interference. In this paper, we propose a real-time depth map enhancement system based on a residual network which uses dual channels to process depth maps and intensity maps respectively and cancels the preprocessing process, and the algorithm proposed can achieve real-time processing speed at more than 30 fps. Furthermore, the FPGA design and implementation for depth sensing is also introduced. In this FPGA design, intensity image and depth image are captured by the dual-camera synchronous acquisition system as the input of neural network. Experiments on various depth map restoration shows our algorithms has better performance than existing LRMC, DE-CNN and DDTF algorithms on standard datasets and has a better depth map super-resolution, and our FPGA completed the test of the system to ensure that the data throughput of the USB 3.0 interface of the acquisition system is stable at 226 Mbps, and support dual-camera to work at full speed, that is, 54 fps@ (1280 × 960 + 328 × 248 × 3).

scholarly journals Camera-based localization microscopy optimized with calibrated structured illumination

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Martin Schmidt ◽  
Adam C. Hundahl ◽  
Henrik Flyvbjerg ◽  
Rodolphe Marie ◽  
Kim I. Mortensen
Keyword(s):  
Data Analysis ◽  
Super Resolution ◽  
Wide Field ◽  
Structured Illumination ◽  
Uniform Illumination ◽  
Localization Microscopy ◽  
Localization And Tracking ◽  
Field Imaging ◽  
Wide Field Imaging ◽  
Localization Information

AbstractUntil very recently, super-resolution localization and tracking of fluorescent particles used camera-based wide-field imaging with uniform illumination. Then it was demonstrated that structured illuminations encode additional localization information in images. The first demonstration of this uses scanning and hence suffers from limited throughput. This limitation was mitigated by fusing camera-based localization with wide-field structured illumination. Current implementations, however, use effectively only half the localization information that they encode in images. Here we demonstrate how all of this information may be exploited by careful calibration of the structured illumination. Our approach achieves maximal resolution for given structured illumination, has a simple data analysis, and applies to any structured illumination in principle. We demonstrate this with an only slightly modified wide-field microscope. Our protocol should boost the emerging field of high-precision localization with structured illumination.

scholarly journals Low-Cost Implementation of Bilinear and Bicubic Image Interpolation for Real-Time Image Super-Resolution

2020 ◽  
Author(s):  
Donya Khaledyan ◽  
Abdolah Amirany ◽  
Kian Jafari ◽  
Mohammad Hossein Moaiyeri ◽  
Abolfazl Zargari Khuzani ◽  
...  
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Super Resolution ◽  
Image Interpolation ◽  
Real Time Image ◽  
Image Super Resolution ◽  
Time Image

Research on the Distributed Characteristics of the Delay for Network Coding Based Real-Time Multicast in MANETs

2014 ◽  
Vol 530-531 ◽  
pp. 768-772
Author(s):  
Guo Ping Tan ◽  
Lin Feng Tan ◽  
Lei Cao ◽  
Mei Yan Ju
Keyword(s):  
Maximum Likelihood ◽  
Probability Distribution ◽  
Network Coding ◽  
Real Time ◽  
Lognormal Distribution ◽  
Ad Hoc ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Actual Distribution ◽  
Delay Distribution

For the study of the applications of partial network coding based real-time multicast protocol (PNCRM) in Mobile Ad hoc networks, the researches should be developed in the probability distribution of delay. In this paper, NS2 is used to obtain the delay of data packets through simulations. Because the delay does not obey the strict normal distribution, the maximum likelihood estimate method based on the lognormal distribution is used to process the data. Using MATLAB to obtain the actual distribution of the natural logarithm of delay, then drawing the delay distribution with the maximum likelihood estimation method based on the lognormal distribution, the conclusion that the distributions obtained by the above mentioned methods are basically consistent can be obtained. So the delay distribution of PNCRM meets the lognormal distribution and the characteristic of delay probability distribution can be estimated.

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