Computational imaging
Computational imaging is the process of indirectly forming images from measurements using algorithms that rely on a significant amount of computing. In contrast to traditional imaging, computational i
Multidimensional signal restoration
In multidimensional signal processing, Multidimensional signal restoration refers to the problem of estimating the original input signal from observations of the distorted or noise contaminated versio
CT scan
A computed tomography scan (usually abbreviated to CT scan; formerly called computed axial tomography scan or CAT scan) is a medical imaging technique used to obtain detailed internal images of the bo
3D sound reconstruction
3D sound reconstruction is the application of reconstruction techniques to 3D sound localization technology. These methods of reconstructing three-dimensional sound are used to recreate sounds to matc
Sonar signal processing
Sonar systems are generally used underwater for range finding and detection. Active sonar emits an acoustic signal, or pulse of sound, into the water. The sound bounces off the target object and retur
Video processing
In electronics engineering, video processing is a particular case of signal processing, in particular image processing, which often employs video filters and where the input and output signals are vid
Computational microscopy
Computational microscopy is a subfield of computational imaging, which combines algorithmic reconstruction with sensing to capture microscopic images of objects. The algorithms used in computational m
Multidimensional system
In mathematical systems theory, a multidimensional system or m-D system is a system in which not only one independent variable exists (like time), but there are several independent variables. Importan
Non-separable wavelet
Non-separable wavelets are multi-dimensional wavelets that are not directly implemented as tensor products of wavelets on some lower-dimensional space.They have been studied since 1992.They offer a fe
Adaptive beamformer
An adaptive beamformer is a system that performs adaptive spatial signal processing with an array of transmitters or receivers. The signals are combined in a manner which increases the signal strength
2D Z-transform
The 2D Z-transform, similar to the Z-transform, is used in Multidimensional signal processing to relate a two-dimensional discrete-time signal to the complex frequency domain in which the 2D surface i
Multidimensional discrete convolution
In signal processing, multidimensional discrete convolution refers to the mathematical operation between two functions f and g on an n-dimensional lattice that produces a third function, also of n-dim
Numerical modeling in echocardiography
Numerical manipulation of Doppler parameters obtain during routine Echocardiography has been extensively utilized to non-invasively estimate intra-cardiac pressures, in many cases removing the need fo
Relative Atrial Index
The Relative Atrial Index (RAI) is a numeric parameter used to assess for cardiac shunt defects. It is calculated from the standard transthoracic Doppler echocardiogram measurements of the right atria
Towed array sonar
A towed array sonar is a system of hydrophones towed behind a submarine or a surface ship on a cable. Trailing the hydrophones behind the vessel, on a cable that can be kilometers long, keeps the arra
Crowther criterion
The conventional method to evaluate the resolution of a tomography reconstruction is determined by the Crowther criterion.The minimum number of views, m, to reconstruct a particle of diameter D to a r
Multidimensional modulation
Multidimensional modulation (MD modulation) is modifying or multiplying an MD signal (typically sinusoidal and referred to as the carrier signal) with another signal that carries some information or m
SAMV (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 tomog
Multidimensional sampling
In digital signal processing, multidimensional sampling is the process of converting a function of a into a discrete collection of values of the function measured on a discrete set of points. This art
Two-dimensional window design
Windowing is a process where an index-limited sequence has its maximum energy concentrated in a finite frequency interval. This can be extended to an N-dimension where the N-D window has the limited s
Doppler echocardiography
Doppler echocardiography is a procedure that uses Doppler ultrasonography to examine the heart. An echocardiogram uses high frequency sound waves to create an image of the heart while the use of Doppl
Wavelet for multidimensional signals analysis
Wavelets are often used to analyse piece-wise smooth signals. Wavelet coefficients can efficiently represent a signal which has led to data compression algorithms using wavelets. Wavelet analysis is e
Two-dimensional filter
Two dimensional filters have seen substantial development effort due to their importance and high applicability across several domains. In the 2-D case the situation is quite different from the 1-D ca
Fast Algorithms for Multidimensional Signals
Similar to 1-D Digital signal processing in case of the Multidimensional signal processing we have Efficient algorithms. The efficiency of an Algorithm can be evaluated by the amount of computational
Electron tomography
Electron tomography (ET) is a tomography technique for obtaining detailed 3D structures of sub-cellular, macro-molecular, or materials specimens. Electron tomography is an extension of traditional tra
Hexagonal fast Fourier transform
The fast Fourier transform (FFT) is an important tool in the fields of image and signal processing. The hexagonal fast Fourier transform (HFFT) uses existing FFT routines to compute the discrete Fouri
Multidimensional signal processing
In signal processing, multidimensional signal processing covers all signal processing done using multidimensional signals and systems. While multidimensional signal processing is a subset of signal pr
Multidimensional spectral estimation
Multidimension spectral estimation is a generalization of spectral estimation, normally formulated for one-dimensional signals, to multidimensional signals or multivariate data, such as wave vectors.
Electrical resistivity tomography
Electrical resistivity tomography (ERT) or electrical resistivity imaging (ERI) is a geophysical technique for imaging sub-surface structures from electrical resistivity measurements made at the surfa
Imaging radar
Imaging radar is an application of radar which is used to create two-dimensional images, typically of landscapes. Imaging radar provides its light to illuminate an area on the ground and take a pictur
Dose-fractionation theorem
The dose-fractionation theorem for tomographic imaging is a statement that says the total dose required to achieve statistical significance for each voxel of a computed 3D reconstruction is the same a
Array processing
Array processing is a wide area of research in the field of signal processing that extends from the simplest form of 1 dimensional line arrays to 2 and 3 dimensional array geometries. Array structure
Multidimensional transform
In mathematical analysis and applications, multidimensional transforms are used to analyze the frequency content of signals in a domain of two or more dimensions.
YaDICs
YaDICs is a program written to perform digital image correlation on 2D and 3D tomographic images. The program was designed to be both modular, by its plugin strategy and efficient, by it multithreadin
Tomographic reconstruction
Tomographic reconstruction is a type of multidimensional inverse problem where the challenge is to yield an estimate of a specific system from a finite number of projections. The mathematical basis fo
Monopulse radar
Monopulse radar is a radar system that uses additional encoding of the radio signal to provide accurate directional information. The name refers to its ability to extract range and direction from a si