Single-image super-resolution via joint statistic models-guided deep auto-encoder network
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3886-2
Abstract: Recent researches on super-resolution (SR) with deep learning networks have achieved amazing results. However, most of the existing studies neglect the internal distinctiveness of an image and the output of most methods tends to be… read more here.
Keywords: image; network; super resolution; model ... 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
Adaptive dehazing control factor based fast single image dehazing
Sign Up to like & getrecommendations! Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-08120-z
Abstract: The single image dehazing is performed using atmospheric scattering model (ASM). The ASM is based on transmission and atmospheric light. Thus, accurate estimation of transmission is essential for quality single image dehazing. Single image dehazing… read more here.
Keywords: image; dehazing control; image dehazing; control factor ... See more keywords
CSIDNet: Compact single image dehazing network for outdoor scene enhancement
Sign Up to like & getrecommendations! Published in 2020 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-09496-z
Abstract: This paper proposes a novel deep learning-based single image dehazing network named as Compact Single Image Dehazing Network (CSIDNet) for outdoor scene enhancement. CSIDNet directly outputs a haze-free image from the given hazy input. The… read more here.
Keywords: image; image dehazing; csidnet; dehazing network ... See more keywords
Conditional generative adversarial network with densely-connected residual learning for single image super-resolution
Sign Up to like & getrecommendations! Published in 2021 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-09817-2
Abstract: Recently, generative adversarial network (GAN) has been widely employed in single image super-resolution (SISR), achieving favorably good perceptual effects. However, the SR outputs generated by GAN still have some fictitious details, which are quite different… read more here.
Keywords: adversarial network; resolution; generative adversarial; single image ... See more keywords
Visibility restoration of single image captured in dust and haze weather conditions
Sign Up to like & getrecommendations! Published in 2020 at "Multidimensional Systems and Signal Processing"
DOI: 10.1007/s11045-019-00678-z
Abstract: Inclement weather existence of fog, haze, and dust generally degrades the visibility of outdoor images. Bad visibility may cause failure in computer vision applications. Existing dehazing methods cannot work well on dust haze images. Such… read more here.
Keywords: haze images; haze; visibility; single image ... See more keywords
Learning Single-Image 3D Reconstruction by Generative Modelling of Shape, Pose and Shading
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Computer Vision"
DOI: 10.1007/s11263-019-01219-8
Abstract: We present a unified framework tackling two problems: class-specific 3D reconstruction from a single image, and generation of new 3D shape samples. These tasks have received considerable attention recently; however, most existing approaches rely on… read more here.
Keywords: reconstruction; shape; supervised methods; shape pose ... See more keywords
A fast single-image super-resolution via directional edge-guided regularized extreme learning regression
Sign Up to like & getrecommendations! Published in 2017 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-016-1045-8
Abstract: The goal of super-resolution (SR) is to increase the spatial resolution of a low-resolution (LR) image by a certain factor using either single or multiple LR input images. This paper presents a machine learning-based approach… read more here.
Keywords: resolution; directional edge; image; regularized extreme ... See more keywords
Single-image super-resolution reconstruction using dark channel regularization network
Sign Up to like & getrecommendations! Published in 2021 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-020-01762-9
Abstract: For single-image super-resolution (SR), deep learning-based approaches have attained superior performance that overshadow all previous approaches. Most recently published deep learning-based single-image SR approaches rely on either deeper or more complex network to achieve further… read more here.
Keywords: resolution; image; network; single image ... See more keywords
Single image defogging based on particle swarm optimization
Sign Up to like & getrecommendations! Published in 2017 at "Optoelectronics Letters"
DOI: 10.1007/s11801-017-7189-0
Abstract: Due to the lack of enough information to solve the equation of image degradation model, existing defogging methods generally introduce some parameters and set these values fixed. Inappropriate parameter setting leads to difficulty in obtaining… read more here.
Keywords: based particle; image; swarm optimization; particle swarm ... See more keywords
Single-image crowd counting: a comparative survey on deep learning-based approaches
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Multimedia Information Retrieval"
DOI: 10.1007/s13735-019-00181-y
Abstract: Crowd counting is an attracting computer vision problem. Solutions to crowd counting hold high adaptability to other counting problems such as traffic counting and cell counting. Numerous methods have been proposed for the problem. Deep… read more here.
Keywords: image crowd; deep learning; crowd counting; learning based ... See more keywords