Results 81 to 90 of about 750,933 (209)
Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networks [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017 Convolutional neural networks have recently demonstrated high-quality reconstruction for single image super-resolution. However, existing methods often require a large number of network parameters and entail heavy computational loads at runtime for ...
Wei-Sheng Lai +3 more
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Super-Resolution with compressively sensed MR/PET signals at its input
Informatics in Medicine Unlocked, 2020 The aim of this paper is to present a highly effective Magnetic Resonance Imaging- Positron Emission Tomography (MR/PET) image reconstruction strategy allowing for simultaneous resolution enhancing and scanning time minimisation.
Krzysztof Malczewski
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Remote Sensing Image Super-resolution Based on Sparse Representation
MATEC Web of Conferences, 2018 In order to obtain higher resolution remote sensing images with more details, an improved sparse representation remote sensing image super-resolution reconstruction(SRR) algorithm is proposed.
Zhu Fuzhen +3 more
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, 2021 This study presents a chronological overview of the single image super-resolution problem. We first define the problem thoroughly and mention some of the serious challenges. Then the problem formulation and the performance metrics are defined. We give an overview of the previous methods relying on reconstruction based solutions and then continue with ...
Ataman, Baran, Seker, Mert, Mckee, David
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Diffusion Models, Image Super-Resolution, and Everything: A Survey [PDF]
IEEE Transactions on Neural Networks and Learning SystemsDiffusion models (DMs) have disrupted the image super-resolution (SR) field and further closed the gap between image quality and human perceptual preferences.
Brian B. Moser +5 more
semanticscholar +1 more source
Geocarto InternationalDespite natural image super-resolution (SR) methods have achieved great success, super-resolution methods for hyperspectral image (HSI) with rich spectral features are still a very challenging task.
Lijing Bu +3 more
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Adaptive Markov Random Fields for Example-Based Super-resolution of Faces
EURASIP Journal on Advances in Signal Processing, 2006 Image enhancement of low-resolution images can be done through methods such as interpolation, super-resolution using multiple video frames, and example-based super-resolution.
Stephenson Todd A, Chen Tsuhan
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Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize?
EURASIP Journal on Advances in Signal Processing, 2007 In multiple-image super-resolution, a high-resolution image is estimated from a number of lower-resolution images. This usually involves computing the parameters of a generative imaging model (such as geometric and photometric registration, and blur) and
Andrew Zisserman +3 more
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Neuromorphic Imaging With Super-Resolution
IEEE Transactions on Circuits and Systems for Video TechnologyNeuromorphic imaging is an emerging technique that imitates the human retina to sense variations in dynamic scenes. It responds to pixel-level brightness changes by asynchronous streaming events and boasts microsecond temporal precision over a high dynamic range, yielding blur-free recordings under extreme illumination.
Pei Zhang +4 more
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Image super‐resolution via dynamic network
CAAI Transactions on Intelligence TechnologyConvolutional neural networks depend on deep network architectures to extract accurate information for image super‐resolution. However, obtained information of these convolutional neural networks cannot completely express predicted high‐quality images ...
Chunwei Tian +4 more
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