scholarly journals Real-time optical reconstruction for three dimensional light-field display based on path-tracing and CNN super-resolution

2021 ◽  
Author(s):  
Xiao Guo ◽  
Xinzhu Sang ◽  
Duo Chen ◽  
Peng Wang ◽  
HUACHUN WANG ◽  
...  
Author(s):  
Wei Gao ◽  
Linjie Zhou ◽  
Lvfang Tao

View synthesis (VS) for light field images is a very time-consuming task due to the great quantity of involved pixels and intensive computations, which may prevent it from the practical three-dimensional real-time systems. In this article, we propose an acceleration approach for deep learning-based light field view synthesis, which can significantly reduce calculations by using compact-resolution (CR) representation and super-resolution (SR) techniques, as well as light-weight neural networks. The proposed architecture has three cascaded neural networks, including a CR network to generate the compact representation for original input views, a VS network to synthesize new views from down-scaled compact views, and a SR network to reconstruct high-quality views with full resolution. All these networks are jointly trained with the integrated losses of CR, VS, and SR networks. Moreover, due to the redundancy of deep neural networks, we use the efficient light-weight strategy to prune filters for simplification and inference acceleration. Experimental results demonstrate that the proposed method can greatly reduce the processing time and become much more computationally efficient with competitive image quality.


2012 ◽  
Vol 32 (10) ◽  
pp. 1022005
Author(s):  
戴志华 Dai Zhihua ◽  
徐于萍 Xu Yuping ◽  
步敬 Bu Jing ◽  
杨勇 Yang Yong ◽  
赵星 Zhao Xing ◽  
...  

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 81045-81054
Author(s):  
Peng Wang ◽  
Xinzhu Sang ◽  
Duo Chen ◽  
Binbin Yan

2020 ◽  
Vol 12 (535) ◽  
pp. eaay0071 ◽  
Author(s):  
Zhen Liu ◽  
Quynh P. H. Nguyen ◽  
Qingxu Guan ◽  
Alexandra Albulescu ◽  
Lauren Erdman ◽  
...  

Airway clearance of pathogens and particulates relies on motile cilia. Impaired cilia motility can lead to reduction in lung function, lung transplant, or death in some cases. More than 50 proteins regulating cilia motility are linked to primary ciliary dyskinesia (PCD), a heterogeneous, mainly recessive genetic lung disease. Accurate PCD molecular diagnosis is essential for identifying therapeutic targets and for initiating therapies that can stabilize lung function, thereby reducing socioeconomic impact of the disease. To date, PCD diagnosis has mainly relied on nonquantitative methods that have limited sensitivity or require a priori knowledge of the genes involved. Here, we developed a quantitative super-resolution microscopy workflow: (i) to increase sensitivity and throughput, (ii) to detect structural defects in PCD patients’ cells, and (iii) to quantify motility defects caused by yet to be found PCD genes. Toward these goals, we built a localization map of PCD proteins by three-dimensional structured illumination microscopy and implemented quantitative image analysis and machine learning to detect protein mislocalization, we analyzed axonemal structure by stochastic optical reconstruction microscopy, and we developed a high-throughput method for detecting motile cilia uncoordination by rotational polarity. Together, our data show that super-resolution methods are powerful tools for improving diagnosis of motile ciliopathies.


2017 ◽  
Author(s):  
Margaret J. Grant ◽  
Matthew S. Loftus ◽  
Aiola P. Stoja ◽  
Dean H. Kedes ◽  
Malcolm Mitchell Smith

By tethering their circular genomes (episomes) to host chromatin, DNA tumor viruses ensure retention and segregation of their genetic material during cell divisions. Despite functional genetic and crystallographic studies, there is little information addressing the three-dimensional structure of these tethers in cells, issues critical for understanding persistent infection by these viruses. Here, we have applied direct stochastic optical reconstruction microscopy (dSTORM) to establish the nanoarchitecture of tethers within cells latently infected with the oncogenic human pathogen, Kaposi's sarcoma-associated herpesvirus (KSHV). Each KSHV tether comprises a series of homodimers of the latency-associated nuclear antigen (LANA) that bind with their C-termini to the tandem array of episomal terminal repeats (TRs) and with their N-termini to host chromatin. Super-resolution imaging revealed that individual KSHV tethers possess similar overall dimensions and, in aggregate, fold to occupy the volume of a prolate ellipsoid. Using plasmids with increasing numbers of TRs, we found that tethers display polymer power-law scaling behavior with a scaling exponent characteristic of active chromatin. For plasmids containing a two-TR tether, we determined the size, separation, and relative orientation of two distinct clusters of bound LANA, each corresponding to a single TR. From these data, we have generated a three-dimensional model of the episomal half of the tether that integrates and extends previously established findings from epi-fluorescent, crystallographic, and epigenetic approaches. Our findings also validate the use of dSTORM in establishing novel structural insights into the physical basis of molecular connections linking host and pathogen genomes.


2018 ◽  
Vol 15 (1) ◽  
pp. 172988141774844 ◽  
Author(s):  
Mandan Zhao ◽  
Gaochang Wu ◽  
Yebin Liu ◽  
Xiangyang Hao

With the development of consumer light field cameras, the light field imaging has become an extensively used method for capturing the three-dimensional appearance of a scene. The depth estimation often requires a dense sampled light field in the angular domain or a high resolution in the spatial domain. However, there is an inherent trade-off between the angular and spatial resolutions of the light field. Recently, some studies for super-resolving the trade-off light field have been introduced. Rather than the conventional approaches that optimize the depth maps, these approaches focus on maximizing the quality of the super-resolved light field. In this article, we investigate how the depth estimation can benefit from these super-resolution methods. Specifically, we compare the qualities of the estimated depth using (a) the original sparse sampled light fields and the reconstructed dense sampled light fields, and (b) the original low-resolution light fields and the high-resolution light fields. Experiment results evaluate the enhanced depth maps using different super-resolution approaches.


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