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
Blurry Facial-Image Deconvolution via Model-Guided Deep Neural Network Inspired From Edge Regularization
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Cognitive and Developmental Systems"
DOI: 10.1109/tcds.2022.3157766
Abstract: The blind facial-image deconvolution problem is ill-posed so that the estimation of latent image and blur kernel is hard to obtain without additional priors or heuristics. Although data-driven methods with deep neural networks have achieved… read more here.
Keywords: image deconvolution; model guided; deep neural; image ... 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
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
Enhancing spatial resolution of BOTDR sensors using image deconvolution.
Sign Up to like & getrecommendations! Published in 2022 at "Optics express"
DOI: 10.1364/oe.459519
Abstract: We propose to employ the image deconvolution technique for Brillouin optical time domain reflectometry (BOTDR) systems to achieve a flexible and enhanced spatial resolution with pump pulses longer than phonon lifetime. By taking the measured… read more here.
Keywords: botdr; spatial resolution; resolution; image deconvolution ... See more keywords
Partially interpretable image deconvolution framework based on the Richardson-Lucy model.
Sign Up to like & getrecommendations! Published in 2023 at "Optics letters"
DOI: 10.1364/ol.478885
Abstract: Fluorescence microscopy typically suffers from aberration induced by system and sample, which could be circumvented by image deconvolution. We proposed a novel, to the best of our knowledge, Richardson-Lucy (RL) model-driven deconvolution framework to improve… read more here.
Keywords: deconvolution; framework; image deconvolution; richardson lucy ... See more keywords