Indirectly forming images from measurements using algorithms
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 imaging systems involve a tight integration of the sensing system and the computation in order to form the images of interest. The ubiquitous availability of fast computing platforms (such as multi-core CPUs and GPUs), the advances in algorithms and modern sensing hardware is resulting in imaging systems with significantly enhanced capabilities. Computational Imaging systems cover a broad range of applications include computational microscopy,[1] tomographic imaging, MRI, ultrasound imaging, computational photography, Synthetic Aperture Radar (SAR), seismic imaging etc. The integration of the sensing and the computation in computational imaging systems allows for accessing information which was otherwise not possible. For example:
A single X-ray image does not reveal the precise location of fracture, but a CT scan which works by combining multiple X-ray images can determine the precise location of one in 3D
A typical camera image cannot image around corners. However, by designing a set-up that involves sending fast pulses of light, recording the received signal and using an algorithm, researchers have demonstrated the first steps in building such a system.[2]
Computational imaging systems also enable system designers to overcome some hardware limitations of optics and sensors (resolution, noise etc.) by overcoming challenges in the computing domain. Some examples of such systems include coherent diffractive imaging, coded-aperture imaging and image super-resolution.
Computational imaging differs from image processing in a sense that the primary goal of the former is to reconstruct human-recognizable images from measured data via algorithms while the latter is to process already-recognizable images (that may be not sufficient in quality) to improve the quality or derive some information from them.
traditional imaging, computationalimaging systems involve a tight integration of the sensing system and the computation in order to form the images of interest...
common computationalimaging techniques are lensless imaging, computational speckle imaging, ptychography and Fourier ptychography. Computationalimaging technique...
CPUs and graphics processing units (GPUs) in this role. ComputationalimagingComputational photography Computer audition Egocentric vision Machine vision...
field of ComputationalImaging. She led the development of an algorithm for imaging black holes, known as Continuous High-resolution Image Reconstruction...
Computational biology refers to the use of data analysis, mathematical modeling and computational simulations to understand biological systems and relationships...
Cleveland, Ohio, USA and founding director of CWRU's Center for ComputationalImaging and Personalized Diagnostics (CCIPD). He is also a Research Scientist...
Computational microscopy is a subfield of computationalimaging, which combines algorithmic reconstruction with sensing to capture microscopic images...
Computational science, also known as scientific computing, technical computing or scientific computation (SC), is a division of science that uses advanced...
Fourier ptychography is a computationalimaging technique based on optical microscopy that consists in the synthesis of a wider numerical aperture from...
Examples of biomedical data science research include: Computational genomics Computationalimaging Electronic health records data mining Biomedical network...
Computational Engineering is an emerging discipline that deals with the development and application of computational models for engineering, known as Computational...
of the next generation of imaging systems, with applications such as high dynamic range (HDR) imaging, compact computational cameras, hyper-spectral cameras...
knowledge from medical images. While closely related to the field of medical imaging, MIC focuses on the computational analysis of the images, not their acquisition...
contributions to the advancement of computational microscopy and its applications Waller, Laura Anne (2010). Computational phase imaging based on intensity transport...
accepted definition of computational intelligence. Generally, computational intelligence is a set of nature-inspired computational methodologies and approaches...
editor-in-chief of IEEE Transactions on Image Processing. He is the father of computationalimaging scientist Katie Bouman. Bouman is the lead author of what has been...
named OSA Fellow in the 2020 class for outstanding inventions in computationalimaging and sensing, including unprecedented demonstrations of the utility...
applied computationalimaging to coherent optical microscopy by solving the inverse problem for OCT. This allows for three-dimensional imaging with extended...
(/t(ʌ)ɪˈkogræfi/ t(a)i-KO-graf-ee)[citation needed] is a computational method of microscopic imaging. It generates images by processing many coherent interference patterns...
project Athena aiming to explore the Central Nervous System using computationalimaging. He has published more than 60 journals and more than 180 conferences...
data science, and computationalimaging", and an IEEE Fellow in 2022 "for contributions to the foundations of computationalimaging and large-scale data...
more specifically in computability theory and computational complexity theory, a model of computation is a model which describes how an output of a mathematical...
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