Blind Text Image Deblurring Algorithm Based on Multi-Scale Fusion and Sparse Priors
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3245150
Abstract: The goal of blind text image deblurring is to obtain a clean text image from the given blurry text image without knowing the blur kernel. Sparsity-based methods have been shown their effectiveness in various blind… read more here.
Keywords: blur kernel; image deblurring; blind text; text image ... 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
Deep Joint Estimation Network for Satellite Video Super-Resolution With Multiple Degradations
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3163790
Abstract: Super-resolution (SR) for satellite video data has been a hot research topic in the field of remote sensing video analysis. The existing satellite video SR methods assume that the blur kernel in the imaging degradation… read more here.
Keywords: video; super resolution; blur kernel; joint estimation ... See more keywords
Blind Superresolution of Satellite Videos by Ghost Module-Based Convolutional Networks
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3233099
Abstract: Deep learning (DL)-based video satellite superresolution (SR) methods have recently yielded superior performance over traditional model-based methods by using an end-to-end manner. Existing DL-based methods usually assume that the blur kernels are known and, thus,… read more here.
Keywords: blur kernel; ghost module; module based; satellite videos ... See more keywords
Partial Deconvolution With Inaccurate Blur Kernel
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2017.2764261
Abstract: Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation.… read more here.
Keywords: inaccurate blur; blur kernel; deconvolution; partial deconvolution ... See more keywords
Blur kernel estimation using sparsity and local smoothness prior
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Electronic Imaging"
DOI: 10.1117/1.jei.26.3.033024
Abstract: Abstract. Since blur kernel estimation is an ill-posed problem, it is essential that it be constrained by parametric image priors. However, the previous normalized sparsity measure alters the kernel structure during estimation. To address the… read more here.
Keywords: estimation; smoothness prior; kernel estimation; blur kernel ... See more keywords
Kernel-attentive weight modulation memory network for optical blur kernel-aware image super-resolution.
Sign Up to like & getrecommendations! Published in 2023 at "Optics letters"
DOI: 10.1364/ol.488562
Abstract: Recently, imaging systems have exhibited remarkable image restoration performance through optimized optical systems and deep-learning-based models. Despite advancements in optical systems and models, severe performance degradation occurs when the predefined optical blur kernel differs from… read more here.
Keywords: blur; blur kernel; optical blur; modulation ... See more keywords
Blur Kernel Estimation by Structure Sparse Prior
Sign Up to like & getrecommendations! Published in 2020 at "Applied Sciences"
DOI: 10.3390/app10020657
Abstract: Blind image deblurring tries to recover a sharp version from a blurred image, where blur kernel is usually unknown. Recently, sparse representation has been successfully applied to estimate the blur kernel. However, the sparse representation… read more here.
Keywords: sparse representation; kernel estimation; blur kernel; structure ... See more keywords