Results 41 to 50 of about 15,742 (208)
Fast and easy blind deblurring using an inverse filter and PROBE
, 2017 PROBE (Progressive Removal of Blur Residual) is a recursive framework for blind deblurring. Using the elementary modified inverse filter at its core, PROBE's experimental performance meets or exceeds the state of the art, both visually and quantitatively.
J Kotera +11 more
core +1 more source
Reference-Based Multi-Level Features Fusion Deblurring Network for Optical Remote Sensing Images
Remote Sensing, 2022 Blind image deblurring is a long-standing challenge in remote sensing image restoration tasks. It aims to recover a latent sharp image from a blurry image while the blur kernel is unknown.
Zhiyuan Li +4 more
doaj +1 more source
Learning Blind Motion Deblurring
, 2017 As handheld video cameras are now commonplace and available in every smartphone, images and videos can be recorded almost everywhere at anytime. However, taking a quick shot frequently yields a blurry result due to unwanted camera shake during recording ...
Hirsch, Michael +3 more
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Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal [PDF]
, 2015 In this paper, we address the problem of estimating and removing non-uniform motion blur from a single blurry image. We propose a deep learning approach to predicting the probabilistic distribution of motion blur at the patch level using a convolutional ...
Cao, Wenfei +3 more
core +5 more sources
Image Quality Improvements Based on Motion-Based Deblurring for Single-Photon Imaging
IEEE Access, 2021 Photon counting imaging can be used to capture clearly photon-limited scenes. In photon counting imaging, information on incident photons is obtained as binary frames (bit-plane frames), which are transformed into a multi-bit image in the reconstruction ...
Kiyotaka Iwabuchi +2 more
doaj +1 more source
Blind Image Deblurring via Reweighted Graph Total Variation
, 2017 Blind image deblurring, i.e., deblurring without knowledge of the blur kernel, is a highly ill-posed problem. The problem can be solved in two parts: i) estimate a blur kernel from the blurry image, and ii) given estimated blur kernel, de-convolve blurry
Bai, Yuanchao +3 more
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Magnetic Resonance in Medicine, EarlyView.ABSTRACT Purpose To develop a generative diffusion model‐based approach for robust and efficient quantitative susceptibility mapping (QSM) reconstruction in intracranial hemorrhage (ICH), applicable to both standard gradient echo (GRE) and rapid echo planar imaging (EPI) acquisitions.
Zhuang Xiong +6 more
wiley +1 more source
An improved nonlocal sparse regularization-based image deblurring via novel similarity criteria
International Journal of Advanced Robotic Systems, 2018 Image deblurring is a challenging problem in image processing, which aims to reconstruct an original high-quality image from its blurred measurement caused by various factors, for example, imperfect focusing caused by the imaging system or different ...
Nannan Wang +3 more
doaj +1 more source
Recent Progress in Image Deblurring [PDF]
, 2014 This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques.
Tao, Dacheng, Wang, Ruxin
core
Microscopy Today, 1998 Abstract If you are an optical microscopist, chances are you have sometimes wished for a way to increase the depth of focus of your images. In this article I describe a method that does this using a simple combination of functions built into most image processing software - so it will not cost you very much to try, The method, however ...
openaire +1 more source