Low Cost Super-Resolution Scaling for Images with Over-Exposed and Saturated Scenes

Author(s):  
Kai-Tse Cheng ◽  
Chung-Hsun Huang ◽  
Yuan-Sun Chu ◽  
Bo-Chao Cheng ◽  
Pin-Sheng Cheng Chou
Keyword(s):  
Low Cost ◽  
Author(s):  
Donya Khaledyan ◽  
Abdolah Amirany ◽  
Kian Jafari ◽  
Mohammad Hossein Moaiyeri ◽  
Abolfazl Zargari Khuzani ◽  
...  

2021 ◽  
pp. 200-211
Author(s):  
Guanqun Liu ◽  
Xin Wang ◽  
Daren Zha ◽  
Lei Wang ◽  
Lin Zhao
Keyword(s):  
Low Cost ◽  

2019 ◽  
Vol 12 (03) ◽  
pp. 1950014 ◽  
Author(s):  
Xibin Yang ◽  
Qian Zhu ◽  
Zhenglong Sun ◽  
Gang Wen ◽  
Xin Jin ◽  
...  

Structured illumination microscopy (SIM) is a promising super-resolution technique for imaging subcellular structures and dynamics due to its compatibility with most commonly used fluorescent labeling methods. Structured illumination can be obtained by either laser interference or projection of fringe patterns. Here, we proposed a fringe projector composed of a compact multi-wavelength LEDs module and a digital micromirror device (DMD) which can be directly attached to most commercial inverted fluorescent microscopes and update it into a SIM system. The effects of the period and duty cycle of fringe patterns on the modulation depth of the structured light field were studied. With the optimized fringe pattern, [Formula: see text] resolution improvement could be obtained with high-end oil objectives. Multicolor imaging and dynamics of subcellular organelles in live cells were also demonstrated. Our method provides a low-cost solution for SIM setup to expand its wide range of applications to most research labs in the field of life science and medicine.


Author(s):  
Gustavo M. Callicó ◽  
Rafael Peset Llopis ◽  
Sebastian López ◽  
José Fco López ◽  
Antonio Núñez ◽  
...  

2021 ◽  
Author(s):  
Aleksandra Klimas ◽  
Brendan Gallagher ◽  
Piyumi Wijesekara ◽  
Sinda Fekir ◽  
Donna Stolz ◽  
...  

Abstract Expansion microscopy (ExM) is a powerful imaging strategy that offers a low-cost solution for nanoimaging with conventional microscopes by physically and isotropically magnifying preserved biological specimens embedded in a cross-linked water-swellable hydrogel. Current ExM protocols require prior treatment with specialized reactive anchoring chemicals to link specific labels and biomolecule classes to the gel. In addition, most techniques reportedly use strong Proteinase K to digest endogenous epitopes to enable expansion and are limited by using mechanically fragile gel formulas to expand specimens by at most 4.5× linearly. Here we describe a new ExM framework, Molecule Anchorable Gel-enabled Nanoscale In-situ Fluorescence MicroscopY (MAGNIFY), that uses a mechanically sturdy gel that enables broad retention of nucleic acids, proteins, and lipids without the need for a separate anchoring step. MAGNIFY expands biological specimens up to 11× and facilitates imaging of cells and tissues with effectively ~25-nm-resolution using an ∼280-nm diffraction-limited objective lens on conventional optical microscopes or with ~13 nm-resolution if combined with Super-resolution Optical Fluctuation Imaging (SOFI). Further, MAGNIFY generalizes well across a broad range of biological specimens, providing insight into nanoscopic subcellular structures including synaptic proteins from mouse brain, podocyte foot processes in human kidney, and defects in cilia and basal bodies in drug-treated human lung organoids. MAGNIFY provides a novel advance that expands the precision, utility, accessibility, and generality of subcellular nanoscopy.


2021 ◽  
Vol 21 (3) ◽  
pp. 236-245
Author(s):  
Bongseok Kim ◽  
Youngseok Jin ◽  
Youngdoo Choi ◽  
Jonghun Lee ◽  
Sangdong Kim

This paper proposes low-complexity super-resolution detection for range-vital Doppler estimation frequency-modulated continuous wave (FMCW) radar. In regards to vital radar, and in order to estimate joint range and vital Doppler information such as the human heartbeat and respiration, two-dimensional (2D) detection algorithms such as 2D-FFT (fast Fourier transform) and 2D-MUSIC (multiple signal classification) are required. However, due to the high complexity of 2D full-search algorithms, it is difficult to apply this process to low-cost vital FMCW systems. In this paper, we propose a method to estimate the range and vital Doppler parameters by using 1D-FFT and 1D-MUSIC algorithms, respectively. Among 1D-FFT outputs for range detection, we extract 1D-FFT results based solely on human target information with phase variation of respiration for each chirp; subsequently, the 1D-MUSIC algorithm is employed to obtain accurate vital Doppler results. By reducing the dimensions of the estimation algorithm from 2D to 1D, the computational burden is reduced. In order to verify the performance of the proposed algorithm, we compare the Monte Carlo simulation and root-mean-square error results. The simulation and experiment results show that the complexity of the proposed algorithm is significantly lower than that of an algorithm detecting signals in several regions.


Author(s):  
Li-Wei Kang ◽  
Chia-Mu Yu ◽  
Chih-Yang Lin ◽  
Chia-Hung Yeh

The chapter provides a survey of recent advances in image/video restoration and enhancement via spare representation. Images/videos usually unavoidably suffer from noises due to sensor imperfection or poor illumination. Numerous contributions have addressed this problem from diverse points of view. Recently, the use of sparse and redundant representations over learned dictionaries has become one specific approach. One goal here is to provide a survey of advances in image/video denoising via sparse representation. Moreover, to consider more general types of noise, this chapter also addresses the problems about removals of structured/unstructured components (e.g., rain streaks or blocking artifacts) from image/video. Moreover, image/video quality may be degraded from low-resolution due to low-cost acquisition. Hence, this chapter also provides a survey of recently advances in super-resolution via sparse representation. Finally, the conclusion can be drawn that sparse representation techniques have been reliable solutions in several problems of image/video restoration and enhancement.


Biometrics ◽  
2017 ◽  
pp. 501-528 ◽  
Author(s):  
Li-Wei Kang ◽  
Chia-Mu Yu ◽  
Chih-Yang Lin ◽  
Chia-Hung Yeh

The chapter provides a survey of recent advances in image/video restoration and enhancement via spare representation. Images/videos usually unavoidably suffer from noises due to sensor imperfection or poor illumination. Numerous contributions have addressed this problem from diverse points of view. Recently, the use of sparse and redundant representations over learned dictionaries has become one specific approach. One goal here is to provide a survey of advances in image/video denoising via sparse representation. Moreover, to consider more general types of noise, this chapter also addresses the problems about removals of structured/unstructured components (e.g., rain streaks or blocking artifacts) from image/video. Moreover, image/video quality may be degraded from low-resolution due to low-cost acquisition. Hence, this chapter also provides a survey of recently advances in super-resolution via sparse representation. Finally, the conclusion can be drawn that sparse representation techniques have been reliable solutions in several problems of image/video restoration and enhancement.


2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Christopher J. Rowlands ◽  
Florian Ströhl ◽  
Pedro P. Vallejo Ramirez ◽  
Katharina M. Scherer ◽  
Clemens F. Kaminski

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