Results 201 to 210 of about 30,721 (259)

A Novel Electrical Equipment Status Diagnosis Method Based on Super-Resolution Reconstruction and Logical Reasoning. [PDF]

Sensors (Basel)
Ping P, Yao Q, Guo W, Liao C.
europepmc   +1 more source

Single-image super-resolution reconstruction based on phase-aware visual multi-layer perceptron (MLP). [PDF]

PeerJ Comput Sci
Shi C, Li M, An Z.
europepmc   +1 more source

SRNet-YOLO: A model for detecting tiny and very tiny pests in cotton fields based on super-resolution reconstruction. [PDF]

Front Plant Sci
Yang S, Zhou G, Feng Y, Zhang J, Jia Z.
europepmc   +1 more source

Biometry and volumetry in multi-centric fetal brain MRI: assessing the bias of super-resolution reconstruction

Sanchez T, Mihailov A, Koob M, Girard N, Manchon A, Valenzuela I, Gómez-Chiari M, Martí Juan G, Pron A, Eixarch E, Piella G, González Ballester MA, Camara O, Dunet V, Auzias G, Bach Cuadra M.   +15 more
europepmc   +1 more source

Generalizing the Nonlocal-Means to Super-Resolution Reconstruction [PDF]

IEEE Transactions on Image Processing, 2009
Super-resolution reconstruction proposes a fusion of several low-quality images into one higher quality result with better optical resolution. Classic super-resolution techniques strongly rely on the availability of accurate motion estimation for this fusion task.
Michael Elad, Hiroyuki Takeda, Matan Protter   +2 more
exaly   +3 more sources

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Super-Resolution Image Reconstruction

IEEE Signal Processing Magazine, 2003
Subhasis Chaudhuri
exaly   +3 more sources

Super-resolution reconstruction of hyperspectral images

IEEE Transactions on Image Processing, 2005
Hyperspectral images are used for aerial and space imagery applications, including target detection, tracking, agricultural, and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles, and sensor noise degrade the quality of these images.
Toygar Akgun, Yucel Altunbasak, Russell M. Mersereau   +2 more
openaire   +2 more sources

Stochastic super-resolution image reconstruction

Journal of Visual Communication and Image Representation, 2010
The objective of super-resolution (SR) imaging is to reconstruct a single higher-resolution image based on a set of lower-resolution images that were acquired from the same scene to overcome the limitations of image acquisition process for facilitating better visualization and content recognition.
Jing Tian 0002, Kai-Kuang Ma
openaire   +1 more source

Reconstructed Densenets for Image Super-Resolution

2018 25th IEEE International Conference on Image Processing (ICIP), 2018
Deep learning has been successfully applied to single image super-resolution problem due to its high data fitting ability. However, the trending of deeper layers and wider receptive field to acquire better performance brings high computation complexity and serious information vanishing. To address this problem, we proposed a new Reconstructed DenseNets
Lingfeng Wang 0002, Linwei Qiu, Wei Sui, Chunhong Pan   +3 more
openaire   +1 more source

Super-resolution reconstruction of image sequences

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1999
In an earlier work (1999), we introduced the problem of reconstructing a super-resolution image sequence from a given low resolution sequence. We proposed two iterative algorithms, the R-SD and the R-LMS, to generate the desired image sequence.
Michael Elad, Arie Feuer
openaire   +1 more source