Video super-resolution for dual-mode digital cameras via scene-matched learning

AbstractThis article describes the characteristics and development of materials for magnetooptical (MO) recording. Magneto-optical recording is derived from thermomagnetic recording and readout by the magneto-optical effect. Rare-earth/transition-metal alloys, mostly Tb-Fe-Co, have been used for recording materials in MO discs. MO discs were first put on the market in 1988. Magnetic-field modulation for recording was introduced in MiniDisc (MD) systems in 1992. MO discs have an advantage in durability and achievability, because recording by magnetization reversal is not accompanied by any atomic movement. Magnetically induced super-resolution (MSR), reported in 1991, enabled resolving powers that are higher than the optical limit. MO discs based on MSR were commercialized as 3.5–in. discs for data recording and as 2–in. discs for digital cameras.As extensions of MSR, DWDD (domain-wall displacement detection) and MAMMOS (magnetic amplifying magneto-optical system) have been proposed, in which the marks are expanded during readout for a large signal. DWDD technology has been used in Hi-MDs (high-density MiniDiscs), which were commercialized in 2004 with storage capacities of 1 Gbyte per 64-mm-diameter disc.

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Dual-mode super-resolution imaging with stimulated emission depletion microscopy and fluorescence emission difference microscopy

Applied Optics ◽

10.1364/ao.54.005425 ◽

2015 ◽

Vol 54 (17) ◽

pp. 5425 ◽

Cited By ~ 2

Author(s):

Yifan Wang ◽

Ye Ma ◽

Cuifang Kuang ◽

Yue Fang ◽

Yingke Xu ◽

...

Keyword(s):

Fluorescence Emission ◽

Super Resolution ◽

Stimulated Emission ◽

Dual Mode ◽

Resolution Imaging ◽

Stimulated Emission Depletion

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COMPRESSED SENSING BY ITERATIVE THRESHOLDING OF GEOMETRIC WAVELETS: A COMPARING STUDY

International Journal of Wavelets Multiresolution and Information Processing ◽

10.1142/s0219691311003992 ◽

2011 ◽

Vol 09 (01) ◽

pp. 63-77 ◽

Cited By ~ 6

Author(s):

JIANWEI MA

Keyword(s):

Remote Sensing ◽

Compressed Sensing ◽

Random Matrices ◽

Numerical Experiments ◽

Super Resolution ◽

Fourier Domain ◽

Digital Cameras ◽

Measurement Matrix ◽

Iterative Thresholding ◽

Single Pixel

Recently, a new compressed-sensing (CS) theory for simultaneous sampling and compression of signals has been applied for imaging and remote sensing. The CS makes it possible for us to take super-resolution photos only using one or a few pixels rather than millions of pixels by conventional digital cameras. However, the performances of CS are related to choices of a measurement matrix and a sparse transform. In this paper, we present an experimentally comparing study for the use of different measurement matrices (e.g., random matrices, noiselet transform matrices, and scrambled block Hadamard ensemble) in encoding step and different geometric wavelets (e.g., curvelets and bandlets) in decoding step. Numerical experiments for single-pixel imaging and Fourier-domain multiple-pixel imaging indicate how to choose a suitable CS strategy to reduce the number of measurements and decoding costs.

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Super Resolution: A Simplified Approach Using GANs

Volume 5 - 2020, Issue 9 - September - International Journal of Innovative Science and Research Technology ◽

10.38124/ijisrt20jul185 ◽

2020 ◽

Vol 5 (7) ◽

pp. 188-191

Author(s):

Dr. Naveena C ◽

Thanush M ◽

Vinay N.B ◽

Yaser Ahmed N

Keyword(s):

Computer Vision ◽

Super Resolution ◽

Generative Adversarial Networks ◽

Digital Cameras ◽

Simplified Approach ◽

Resolution Image ◽

Adversarial Networks ◽

Current Scenario ◽

Computer Vision Applications ◽

The Cost

The project entitled “Super-Resolution: A simplified approach using GANs”, aims to construct a Higher Resolution image from a Lower Resolution image, without losing much detail. In other words, it is a process of up-sampling of an under-sampled image. In the current scenario, there is a high reliance on hardware improvements to capture better highresolution images. Although many digital cameras provide enough HR-imagery, the cost to construct and purchase such a high-end camera is high. Also, many computer vision applications like medical imaging, forensic and many more still have a strong demand for higher resolution imagery which is likely to be exceeded by the capabilities of these HR digital cameras we have today. To cope with this demand, a method to generate an HR image is shown using Generative Adversarial Networks (GANs).

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Super-Resolution Image Reconstruction Using Dual-Mode Complex Diffusion-Based Shock Filter and Singular Value Decomposition

Circuits Systems and Signal Processing ◽

10.1007/s00034-016-0470-9 ◽

2016 ◽

Vol 36 (8) ◽

pp. 3409-3425 ◽

Cited By ~ 4

Author(s):

Gunnam Suryanarayana ◽

Ravindra Dhuli

Keyword(s):

Image Reconstruction ◽

Singular Value Decomposition ◽

Super Resolution ◽

Singular Value ◽

Dual Mode ◽

Resolution Image ◽

Complex Diffusion ◽

Shock Filter ◽

Value Decomposition

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Outreach Opportunities Using the Instructional SEM at Iowa State University

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100164520 ◽

1996 ◽

Vol 54 ◽

pp. 412-413

Author(s):

L. S. Chumbley ◽

M. Meyer ◽

K. Fredrickson ◽

F.C. Laabs

Keyword(s):

Materials Science ◽

State University ◽

Digital Cameras ◽

Audio Signals ◽

Iowa State University ◽

Cornell University ◽

Sem Image ◽

Local Schools ◽

Materials Science And Engineering ◽

Video And Audio

The development of a scanning electron microscope (SEM) suitable for instructional purposes has created a large number of outreach opportunities for the Materials Science and Engineering (MSE) Department at Iowa State University. Several collaborative efforts are presently underway with local schools and the Department of Curriculum and Instruction (C&I) at ISU to bring SEM technology into the classroom in a near live-time, interactive manner. The SEM laboratory is shown in Figure 1.Interactions between the laboratory and the classroom use inexpensive digital cameras and shareware called CU-SeeMe, Figure 2. Developed by Cornell University and available over the internet, CUSeeMe provides inexpensive video conferencing capabilities. The software allows video and audio signals from Quikcam™ cameras to be sent and received between computers. A reflector site has been established in the MSE department that allows eight different computers to be interconnected simultaneously. This arrangement allows us to demonstrate SEM principles in the classroom. An Apple Macintosh has been configured to allow the SEM image to be seen using CU-SeeMe.

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