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While deep neural networks (NN) significantly advance image compressed sensing (CS) by improving reconstruction quality, the necessity of training current CS NNs from scratch constrains their effectiveness and hampers rapid deployment.…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Bin Chen , Zhenyu Zhang , Weiqi Li , Chen Zhao , Jiwen Yu , Shijie Zhao , Jie Chen , Jian Zhang

The most ubiquitous form of computational aberration correction for microscopy is deconvolution. However, deconvolution relies on the assumption that the point spread function is the same across the entire field-of-view. This assumption is…

Image and Video Processing · Electrical Eng. & Systems 2025-04-30 Amit Kohli , Anastasios N. Angelopoulos , David McAllister , Esther Whang , Sixian You , Kyrollos Yanny , Federico M. Gasparoli , Bo-Jui Chang , Reto Fiolka , Laura Waller

Structured Illumination Microscopy (SIM) allows access to spatial information beyond the diffraction limit by folding high frequency components into the optical system's base-band. Using various algorithmic techniques, an image containing…

Optics · Physics 2024-10-16 Doron Shterman , Guy Bartal

Since the invention of digital cameras there has been a concerted drive towards detector arrays with higher spatial resolution. Microscanning is a technique that provides a final higher resolution image by combining multiple images of a…

Structured Illumination Microscopy (SIM) overcomes the optical diffraction limit by folding high-frequency components into the baseband of the optical system, where they can be extracted and then repositioned to their original location in…

Optics · Physics 2024-11-18 Doron Shterman , Guy Bartal

Structured illumination microscopy (SIM) improves resolution by down-modulating high-frequency information of an object to fit within the passband of the optical system. Generally, the reconstruction process requires prior knowledge of the…

Computer Vision and Pattern Recognition · Computer Science 2017-01-13 Li-Hao Yeh , Lei Tian , Laura Waller

Magnetic resonance imaging (MRI) reconstruction is an active inverse problem which can be addressed by conventional compressed sensing (CS) MRI algorithms that exploit the sparse nature of MRI in an iterative optimization-based manner.…

Computer Vision and Pattern Recognition · Computer Science 2019-06-13 Yuxiang Dai , Peixian Zhuang

We present an imaging technique that allows the recovery of the transparency profile of wavelength-scale objects with deep subwavelength resolution based on far-field intensity measurements. The approach, interscale mixing microscopy (IMM),…

Optics · Physics 2017-03-21 Sandeep Inampudi , Nicholas Kuhta , Viktor A. Podolskiy

Reflectance Confocal Microscopy (RCM) is a non-invasive imaging technique used in biomedical research and clinical dermatology. It provides virtual high-resolution images of the skin and superficial tissues, reducing the need for physical…

Image and Video Processing · Electrical Eng. & Systems 2024-04-26 Hong-Jun Yoon , Chris Keum , Alexander Witkowski , Joanna Ludzik , Tracy Petrie , Heidi A. Hanson , Sancy A. Leachman

Compressed Sensing MRI reconstructs images of the body's internal anatomy from undersampled measurements, thereby reducing scan time. Recently, deep learning has shown great potential for reconstructing high-fidelity images from highly…

Image and Video Processing · Electrical Eng. & Systems 2025-04-07 Armeet Singh Jatyani , Jiayun Wang , Aditi Chandrashekar , Zihui Wu , Miguel Liu-Schiaffini , Bahareh Tolooshams , Anima Anandkumar

Circular Synthetic aperture sonars (CSAS) capture multiple observations of a scene to reconstruct high-resolution images. We can characterize resolution by modeling CSAS imaging as the convolution between a scene's underlying point…

Image and Video Processing · Electrical Eng. & Systems 2023-06-28 Albert Reed , Thomas Blanford , Daniel C. Brown , Suren Jayasuriya

Compressed sensing (CS) is a valuable technique for reconstructing measurements in numerous domains. CS has not yet gained widespread adoption in scanning tunneling microscopy (STM), despite potentially offering the advantages of lower…

Mesoscale and Nanoscale Physics · Physics 2022-02-09 Brian E. Lerner , Anayeli Flores-Garibay , Benjamin J. Lawrie , Petro Maksymovych

Fiber-based confocal endomicroscopy has shown great promise for minimally-invasive deep-tissue imaging. Despite its advantages, confocal fiber-bundle endoscopy inherently suffers from undersampling due to the spacing between fiber cores,…

Optics · Physics 2023-05-25 Gil Weinberg , Uri Weiss , Ori Katz

Structured illumination microscopy (SIM) provides images of fluorescent objects at an enhanced resolution greater than that of conventional epifluorescence wide-field microscopy. Initially demonstrated in 1999 to enhance the lateral…

Optics · Physics 2022-03-09 James D. Manton

Single-pixel imaging (SPI) is a novel imaging technique whose working principle is based on the compressive sensing (CS) theory. In SPI, data is obtained through a series of compressive measurements and the corresponding image is…

Image and Video Processing · Electrical Eng. & Systems 2022-07-15 Stephen L. H. Lau , Edwin K. P. Chong

Computed tomography (CT) is widely used in scientific imaging systems such as synchrotron and laboratory-based nano-CT, but acquiring full-view sinograms requires high radiation dose and long scan times. Sparse-view CT reduces this burden…

Image and Video Processing · Electrical Eng. & Systems 2026-02-10 Jiaze E , Srutarshi Banerjee , Tekin Bicer , Guannan Wang , Yanfu Zhang , Bin Ren

Widefield microscopy methods applied to optically thick specimens are faced with reduced contrast due to spatial crosstalk, in which the signal at each point is the result of a superposition from neighboring points that are simultaneously…

Lensless imaging is a popular research field for the advantages of small size, wide field-of-view and low aberration in recent years. However, some traditional lensless imaging methods suffer from slow convergence, mechanical errors and…

The lensless endoscope (LE) is a promising device to acquire in vivo images at a cellular scale. The tiny size of the probe enables a deep exploration of the tissues. Lensless endoscopy with a multicore fiber (MCF) commonly uses a spatial…