Papers Image Deconvolution
“Image Deconvolution” 태그가 달린 논문 78편 · 필터 해제
An Adaptive Parameter Estimation for Guided Filter based Image Deconvolution
Image deconvolution is still to be a challenging ill-posed problem for recovering a clear image from a given blurry image, when the point spread function is known. Although competitive deconvolution methods are numerical…
DeblurringDenoisingImage DeconvolutionImage Restoration+1Blind Image Deconvolution by Automatic Gradient Activation
Blind image deconvolution is an ill-posed inverse problem which is often addressed through the application of appropriate prior. Although some priors are informative in general, many images do not strictly conform to thi…
Image DeconvolutionA Framework for Fast Image Deconvolution with Incomplete Observations
In image deconvolution problems, the diagonalization of the underlying operators by means of the FFT usually yields very large speedups. When there are incomplete observations (e.g., in the case of unknown boundaries), s…
DemosaickingImage DeconvolutionReconstruction of Enhanced Ultrasound Images From Compressed Measurements Using Simultaneous Direction Method of Multipliers
High resolution ultrasound image reconstruction from a reduced number of measurements is of great interest in ultrasound imaging, since it could enhance both the frame rate and image resolution. Compressive deconvolution…
compressed sensingImage DeconvolutionImage ReconstructionVideo Super-Resolution via Deep Draft-Ensemble Learning
We propose a new direction for fast video super-resolution (VideoSR) via a SR draft ensemble, which is defined as the set of high-resolution patch candidates before final image deconvolution. Our method contains two main…
Ensemble LearningImage DeconvolutionSuper-ResolutionVideo Super-ResolutionPost-Reconstruction Deconvolution of PET Images by Total Generalized Variation Regularization
Improving the quality of positron emission tomography (PET) images, affected by low resolution and high level of noise, is a challenging task in nuclear medicine and radiotherapy. This work proposes a restoration method,…
Image DeconvolutionDual Domain Filters Based Texture and Structure Preserving Image Non-Blind Deconvolution
Image deconvolution continues to be an active research topic of recovering a sharp image, given a blurry one generated by a convolution. One of the most challenging problems in image deconvolution is how to preserve the …
DeblurringImage DeconvolutionA new Level-set based Protocol for Accurate Bone Segmentation from CT Imaging
In this work it is proposed a medical image segmentation pipeline for accurate bone segmentation from CT imaging. It is a two-step methodology, with a pre-segmentation step and a segmentation refinement step. First, the …
Image CroppingImage DeconvolutionImage SegmentationMedical Image Segmentation+2Deep Convolutional Neural Network for Image Deconvolution
Many fundamental image-related problems involve deconvolution operators. Real blur degradation seldom complies with an deal linear convolution model due to camera noise, saturation, image compression, to name a few. Inst…
Image CompressionImage DeconvolutionModular proximal optimization for multidimensional total-variation regularization
We study \emph{TV regularization}, a widely used technique for eliciting structured sparsity. In particular, we propose efficient algorithms for computing prox-operators for $\ell_p$-norm TV. The most important among the…
DenoisingImage DeconvolutionImage DenoisingVideo DenoisingLearning to Deblur
We describe a learning-based approach to blind image deconvolution. It uses a deep layered architecture, parts of which are borrowed from recent work on neural network learning, and parts of which incorporate computation…
Image DeconvolutionGyro-Based Multi-Image Deconvolution for Removing Handshake Blur
Image deblurring to remove blur caused by camera shake has been intensively studied. Nevertheless, most methods are brittle and computationally expensive. In this paper we analyze multi-image approaches, which capture an…
DeblurringImage DeblurringImage DeconvolutionFTVd is beyond Fast Total Variation regularized Deconvolution
In this paper, we revisit the "FTVd" algorithm for Fast Total Variation Regularized Deconvolution, which has been widely used in the past few years. Both its original version implemented in the MATLAB software FTVd 3.0 a…
Image DeconvolutionA Robust Variational Model for Positive Image Deconvolution
In this paper, an iterative method for robust deconvolution with positivity constraints is discussed. It is based on the known variational interpretation of the Richardson-Lucy iterative deconvolution as fixed-point iter…
Computational EfficiencyImage DeconvolutionImage RestorationHandling Noise in Single Image Deblurring Using Directional Filters
State-of-the-art single image deblurring techniques are sensitive to image noise. Even a small amount of noise, which is inevitable in low-light conditions, can degrade the quality of blur kernel estimation dramatically.…
DeblurringDenoisingImage DeblurringImage Deconvolution+2A Machine Learning Approach for Non-blind Image Deconvolution
Image deconvolution is the ill-posed problem of recovering a sharp image, given a blurry one generated by a convolution. In this work, we deal with space-invariant nonblind deconvolution. Currently, the most successful m…
BIG-bench Machine LearningImage DeconvolutionAlgorithmic Optimisations for Iterative Deconvolution Methods
We investigate possibilities to speed up iterative algorithms for non-blind image deconvolution. We focus on algorithms in which convolution with the point-spread function to be deconvolved is used in each iteration, and…
Image DeconvolutionFast Image Deconvolution using Hyper-Laplacian Priors
The heavy-tailed distribution of gradients in natural scenes have proven effective priors for a range of problems such as denoising, deblurring and super-resolution. However, the use of sparse distributions makes the pro…
DeblurringDenoisingImage DeconvolutionSuper-Resolution