The Sylvester and Bézout Resultant Matrices for Blind Image Deconvolution
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Mathematical Imaging and Vision"
DOI: 10.1007/s10851-018-0812-2
Abstract: Blind image deconvolution ($$\text {BID}$$BID) is one of the most important problems in image processing, and it requires the determination of an exact image $$\mathcal {F}$$F from a degraded form of it $$\mathcal {G}$$G when… read more here.
Keywords: image; image deconvolution; sylvester zout; sylvester ... See more keywords
Blind image quality assessment using a combination of statistical features and CNN
Sign Up to like & getrecommendations! Published in 2020 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-08990-8
Abstract: Blind Image Quality Assessment (BIQA) has been an enticing research problem in image processing, during the last few decades. In spite of the introduction of several BIQA algorithms, quantifying image quality without the help of… read more here.
Keywords: quality; image; image quality; quality assessment ... See more keywords
Blind image deblurring via hybrid deep priors modeling
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.01.004
Abstract: Abstract Blind image deblurring is a challenging low-level vision problem which aims to restore a sharp image only from the blurry observation. Few known information makes this problem fundamentally ill-posed. Most recent works focus on… read more here.
Keywords: hybrid deep; image; deep priors; latent image ... See more keywords
Role of approximation wavelet coefficients in blind image deconvolution
Sign Up to like & getrecommendations! Published in 2018 at "Electronics Letters"
DOI: 10.1049/el.2017.3445
Abstract: The role of approximation coefficients (ACs) in blind image deconvolution (BID) is examined by restoring each sub-band image individually in the wavelet domain, and excellent performance is achieved by an average strategy for the estimation… read more here.
Keywords: image; deconvolution; wavelet; role approximation ... See more keywords
Low Dimensional Manifold Regularization Based Blind Image Inpainting and Non-Uniform Impulse Noise Recovery
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3035532
Abstract: Blind image inpainting is a challenging task in image processing. Motivated by the excellent performance of low dimensional manifold model (LDMM) in image inpainting for large-scale pixels missing, we introduce a novel blind inpainting model… read more here.
Keywords: image inpainting; dimensional manifold; low dimensional; image ... See more keywords
Blind Image Deblurring via Local Maximum Difference Prior
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3039281
Abstract: Blind image deblurring is a well-known conundrum in the digital image processing field. To get a solid and pleasing deblurred result, reasonable statistical prior of the true image and the blur kernel is required. In… read more here.
Keywords: image deblurring; image; maximum difference; local maximum ... See more keywords
Mixture of Gaussian Blur Kernel Representation for Blind Image Restoration
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2017.2706062
Abstract: Blind image restoration is a nonconvex problem involving the restoration of images using unknown blur kernels. The success of the restoration process depends on three factors: first, the amount of prior information concerning the image… read more here.
Keywords: image; image restoration; restoration; blur kernel ... See more keywords
Blind Image Deconvolution Using Deep Generative Priors
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2020.3032671
Abstract: This article proposes a novel approach to regularize the ill-posed and non-linear blind image deconvolution (blind deblurring) using deep generative networks as priors. We employ two separate pretrained generative networks — given lower-dimensional Gaussian vectors… read more here.
Keywords: image deconvolution; deep generative; using deep; image ... See more keywords
A Simple Local Minimal Intensity Prior and an Improved Algorithm for Blind Image Deblurring
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2020.3034137
Abstract: Blind image deblurring is a long standing challenging problem in image processing and low-level vision. Recently, sophisticated priors such as dark channel prior, extreme channel prior, and local maximum gradient prior, have shown promising effectiveness.… read more here.
Keywords: image deblurring; simple local; local minimal; algorithm ... See more keywords
Blind Image Deblurring via Superpixel Segmentation Prior
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2021.3074799
Abstract: We present an effective blind image deblurring algorithm based on superpixel segmentation prior (SSP). The motivation of this work is an interesting observation that the more rough the segmentation boundaries are, the clearer the image… read more here.
Keywords: segmentation prior; superpixel segmentation; image deblurring; segmentation ... See more keywords
Self-Supervised Blind Image Deconvolution via Deep Generative Ensemble Learning
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2022.3207279
Abstract: Blind image deconvolution (BID) is about recovering a latent image with sharp details from its blurred observation generated by the convolution with an unknown smoothing kernel. Recently, deep generative priors from untrained neural networks (NNs)… read more here.
Keywords: ensemble learning; blind image; image deconvolution; deep generative ... See more keywords