Residual attention network using multi-channel dense connections for image super-resolution
Sign Up to like & getrecommendations! Published in 2020 at "Applied Intelligence"
DOI: 10.1007/s10489-020-01723-2
Abstract: In recent years, the methods based on deep convolutional neural networks (DCNN) have greatly promoted the development of image super-resolution (SR). However, deeper and wider SR networks are more difficult to train. For the SR… read more here.
Keywords: resolution; network; multi channel; super resolution ... See more keywords
Deformable and residual convolutional network for image super-resolution
Sign Up to like & getrecommendations! Published in 2021 at "Applied Intelligence"
DOI: 10.1007/s10489-021-02246-0
Abstract: Recent research on image super-resolution (SR) has greatly progressed with the development of convolutional neural networks (CNNs). However, the fixed geometric structures of standard convolution filters largely limit the learning capacity of CNNs for image… read more here.
Keywords: image super; super resolution; image; deformable residual ... See more keywords
Image super-resolution via channel attention and spatial attention
Sign Up to like & getrecommendations! Published in 2022 at "Applied Intelligence"
DOI: 10.1007/s10489-021-02464-6
Abstract: Deep convolutional networks have been widely applied in super-resolution (SR) tasks and have achieved excellent performance. However, even though the self-attention mechanism is a hot topic, has not been applied in SR tasks. In this… read more here.
Keywords: image super; super resolution; via channel; attention ... See more keywords
Depth Image Super Resolution for 3D Reconstruction of Oil Reflnery Buildings
Sign Up to like & getrecommendations! Published in 2019 at "Chemistry and Technology of Fuels and Oils"
DOI: 10.1007/s10553-019-01055-z
Abstract: Time-of-Flight (ToF) camera can collect the depth data of dynamic scene surface in real time, which has been applied to 3D reconstruction of refinery buildings. However; due to the limitations of sensor hardware, the resolution… read more here.
Keywords: reconstruction; resolution; super resolution; depth image ... See more keywords
A Total Fractional-Order Variation Model for Image Super-Resolution and Its SAV Algorithm
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DOI: 10.1007/s10915-020-01185-1
Abstract: Single-image super-resolution reconstruction aims to obtain a high-resolution image from a low-resolution image. Since the super-resolution problem is ill-posed, it is common to use a regularization technique. However, the choice of the fidelity and regularization… read more here.
Keywords: resolution; image; fractional order; super resolution ... See more keywords
Single image super resolution for texture images through neighbor embedding
Sign Up to like & getrecommendations! Published in 2017 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-017-5367-5
Abstract: This article proposes an improved learning based super resolution scheme using manifold learning for texture images. Pseudo Zernike moment (PZM) has been employed to extract features from the texture images. In order to efficiently retrieve… read more here.
Keywords: super resolution; texture images; image super; texture ... See more keywords
Image super-resolution via two stage coupled dictionary learning
Sign Up to like & getrecommendations! Published in 2017 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-017-5493-0
Abstract: Example-based image super-resolution aims to establish a learning model for generating the high resolution image from the coupled training pairs, which is an active study area of mobile media in the recent modern communication. In… read more here.
Keywords: resolution; image; high resolution; super resolution ... See more keywords
A fast single-image super-resolution method implemented with CUDA
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Real-Time Image Processing"
DOI: 10.1007/s11554-018-0774-z
Abstract: Image super-resolution (SR) plays an important role in many areas as it promises to generate high-resolution (HR) images without upgrading image sensors. Many existing SR methods require a large external training set, which would consume… read more here.
Keywords: resolution; image; training set; super resolution ... See more keywords
Droplet Image Super Resolution Based on Sparse Representation and Kernel Regression
Sign Up to like & getrecommendations! Published in 2018 at "Microgravity Science and Technology"
DOI: 10.1007/s12217-018-9597-6
Abstract: Microgravity and containerless conditions, which are produced via electrostatic levitation combined with a drop tube, are important when studying the intrinsic properties of new metastable materials. Generally, temperature and image sensors can be used to… read more here.
Keywords: resolution; image; droplet; super resolution ... See more keywords
Single image super resolution via wavelet transform fusion and SRFeat network
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-020-02065-0
Abstract: Image super resolution is a vital research topic in the field of computer vision. It aims to reconstruct high resolution images from low resolution images. Although the conventional image super resolution methods have achieved good… read more here.
Keywords: resolution; image; network; super resolution ... See more keywords
Applying single-image super-resolution to enhancment of deep-water bathymetry
Sign Up to like & getrecommendations! Published in 2019 at "Heliyon"
DOI: 10.1016/j.heliyon.2019.e02570
Abstract: We present research using single-image super-resolution (SISR) algorithms to enhance knowledge of the seafloor using the 1-minute GEBCO 2014 grid when 100m grids from high-resolution sonar systems are available for training. We performed numerical experiments… read more here.
Keywords: resolution; super resolution; image super; bathymetry ... See more keywords