Super-resolution imaging

super-resolutionsuperresolutionsuper resolutionmage super-resolutionsuper resolution imagingsuperresolve
Super-resolution imaging (SR) is a class of techniques that enhance the resolution of an imaging system.wikipedia
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SAMV (algorithm)

SAMViterative Sparse Asymptotic Minimum Variance
In some radar and sonar imaging applications (e.g., magnetic resonance imaging (MRI), high-resolution computed tomography), subspace decomposition-based methods (e.g., MUSIC ) and compressed sensing-based algorithms (e.g., SAMV ) are employed to achieve SR over standard periodogram algorithm.
SAMV (iterative Sparse Asymptotic Minimum Variance ) is a parameter-free superresolution algorithm for the linear inverse problem in spectral estimation, direction-of-arrival (DOA) estimation and tomographic reconstruction with applications in signal processing, medical imaging and remote sensing.

Magnetic resonance imaging

MRImagnetic resonance imaging (MRI)magnetic resonance
In some radar and sonar imaging applications (e.g., magnetic resonance imaging (MRI), high-resolution computed tomography), subspace decomposition-based methods (e.g., MUSIC ) and compressed sensing-based algorithms (e.g., SAMV ) are employed to achieve SR over standard periodogram algorithm. The approach can take the form of extrapolating the image in the frequency domain, by assuming that the object is an analytic function, and that we can exactly know the function values in some interval. This method is severely limited by the ever-present noise in digital imaging systems, but it can work for radar, astronomy, microscopy or magnetic resonance imaging. More recently, a fast single image super-resolution algorithm based on a closed-form solution to problems has been proposed and demonstrated to accelerate most of the existing Bayesian super-resolution methods significantly.
However, recent compressed sensing-based software algorithms (e.g., SAMV ) have been proposed to achieve super-resolution without requiring such high field strengths.

MUSIC (algorithm)

MUltiple SIgnal ClassificationMUSICMUSIC (Multiple Signal Classification)
In some radar and sonar imaging applications (e.g., magnetic resonance imaging (MRI), high-resolution computed tomography), subspace decomposition-based methods (e.g., MUSIC ) and compressed sensing-based algorithms (e.g., SAMV ) are employed to achieve SR over standard periodogram algorithm.
This is a form of superresolution.

Periodogram

In some radar and sonar imaging applications (e.g., magnetic resonance imaging (MRI), high-resolution computed tomography), subspace decomposition-based methods (e.g., MUSIC ) and compressed sensing-based algorithms (e.g., SAMV ) are employed to achieve SR over standard periodogram algorithm.
MUltiple SIgnal Classification (MUSIC), a popular parametric superresolution method

Digital image processing

image processingimageprocessing
Super-resolution imaging techniques are used in general image processing and in super-resolution microscopy.
Superresolution

Superlens

subwavelength imaginghyperlensmetamaterial lens
The usual discussion of super-resolution involved conventional imagery of an object by an optical system. But modern technology allows probing the electromagnetic disturbance within molecular distances of the source which has superior resolution properties, see also evanescent waves and the development of the new Super lens.
When illuminated near its plasma frequency, the lens could be used for superresolution imaging that compensates for wave decay and reconstructs images in the near-field.

Hyperacuity (scientific term)

hyperacuity
The location of a single source can be determined by computing the "center of gravity" (centroid) of the light distribution extending over several adjacent pixels (see figure on the left). Provided that there is enough light, this can be achieved with arbitrary precision, very much better than pixel width of the detecting apparatus and the resolution limit for the decision of whether the source is single or double. This technique, which requires the presupposition that all the light comes from a single source, is at the basis of what has become known as super-resolution microscopy, e.g. STORM, where fluorescent probes attached to molecules give nanoscale distance information. It is also the mechanism underlying visual hyperacuity.
In computer graphics the phrase “sub-pixel resolution” is sometimes used in discussions of anti-aliasing and geometrical superresolution.

Microscope

microscopesmicroscopicmicroscopically
The approach can take the form of extrapolating the image in the frequency domain, by assuming that the object is an analytic function, and that we can exactly know the function values in some interval. This method is severely limited by the ever-present noise in digital imaging systems, but it can work for radar, astronomy, microscopy or magnetic resonance imaging. More recently, a fast single image super-resolution algorithm based on a closed-form solution to problems has been proposed and demonstrated to accelerate most of the existing Bayesian super-resolution methods significantly.
Much current research (in the early 21st century) on optical microscope techniques is focused on development of superresolution analysis of fluorescently labelled samples.

Deblurring

image deblurringFocus recovery
Deblurring
Super-resolution

Image resolution

resolutionhigh resolutionhigh-resolution
Super-resolution imaging (SR) is a class of techniques that enhance the resolution of an imaging system.

Digital imaging

imagingdigitalelectronic imaging
Super-resolution imaging (SR) is a class of techniques that enhance the resolution of an imaging system.

Image sensor

sensorimage sensorssensors
In some SR techniques—termed optical SR—the diffraction limit of systems is transcended, while in others—geometrical SR—the resolution of digital imaging sensors is enhanced.

Radar

radar stationradarsradar system
In some radar and sonar imaging applications (e.g., magnetic resonance imaging (MRI), high-resolution computed tomography), subspace decomposition-based methods (e.g., MUSIC ) and compressed sensing-based algorithms (e.g., SAMV ) are employed to achieve SR over standard periodogram algorithm. The approach can take the form of extrapolating the image in the frequency domain, by assuming that the object is an analytic function, and that we can exactly know the function values in some interval. This method is severely limited by the ever-present noise in digital imaging systems, but it can work for radar, astronomy, microscopy or magnetic resonance imaging. More recently, a fast single image super-resolution algorithm based on a closed-form solution to problems has been proposed and demonstrated to accelerate most of the existing Bayesian super-resolution methods significantly.

Sonar

asdicvariable depth sonaractive sonar
In some radar and sonar imaging applications (e.g., magnetic resonance imaging (MRI), high-resolution computed tomography), subspace decomposition-based methods (e.g., MUSIC ) and compressed sensing-based algorithms (e.g., SAMV ) are employed to achieve SR over standard periodogram algorithm.

High-resolution computed tomography

high resolution computed tomographyhigh-resolution CThigh resolution CT
In some radar and sonar imaging applications (e.g., magnetic resonance imaging (MRI), high-resolution computed tomography), subspace decomposition-based methods (e.g., MUSIC ) and compressed sensing-based algorithms (e.g., SAMV ) are employed to achieve SR over standard periodogram algorithm.

Space (mathematics)

spacemathematical spacespaces
In some radar and sonar imaging applications (e.g., magnetic resonance imaging (MRI), high-resolution computed tomography), subspace decomposition-based methods (e.g., MUSIC ) and compressed sensing-based algorithms (e.g., SAMV ) are employed to achieve SR over standard periodogram algorithm.

Compressed sensing

compressive sensingcompressed sensing techniquesCompressed-Sensing
In some radar and sonar imaging applications (e.g., magnetic resonance imaging (MRI), high-resolution computed tomography), subspace decomposition-based methods (e.g., MUSIC ) and compressed sensing-based algorithms (e.g., SAMV ) are employed to achieve SR over standard periodogram algorithm.

Diffraction

diffraction patterndiffractdiffracted
Diffraction Limit The detail of a physical object that an optical instrument can reproduce in an image has limits that are mandated by laws of physics, whether formulated by the diffraction equations in the wave theory of light or the Uncertainty Principle for photons in quantum mechanics.

Light

visible lightvisiblelight source
Diffraction Limit The detail of a physical object that an optical instrument can reproduce in an image has limits that are mandated by laws of physics, whether formulated by the diffraction equations in the wave theory of light or the Uncertainty Principle for photons in quantum mechanics.

Uncertainty principle

Heisenberg uncertainty principleuncertainty relationquantum uncertainty
Diffraction Limit The detail of a physical object that an optical instrument can reproduce in an image has limits that are mandated by laws of physics, whether formulated by the diffraction equations in the wave theory of light or the Uncertainty Principle for photons in quantum mechanics.

Quantum mechanics

quantum physicsquantum mechanicalquantum theory
Diffraction Limit The detail of a physical object that an optical instrument can reproduce in an image has limits that are mandated by laws of physics, whether formulated by the diffraction equations in the wave theory of light or the Uncertainty Principle for photons in quantum mechanics.

Maxwell's equations

equationsMaxwell equationselectromagnetic theory
New procedures probing electro-magnetic disturbances at the molecular level (in the so-called near field) remain fully consistent with Maxwell's equations.

Fourier optics

4F correlatorFourier domainFourier phase
In Fourier optics light distributions are expressed as superpositions of a series of grating light patterns in a range of fringe widths, technically spatial frequencies.

Spatial frequency

spatial frequenciesspace frequencyfrequency
In Fourier optics light distributions are expressed as superpositions of a series of grating light patterns in a range of fringe widths, technically spatial frequencies.