Results 51 to 60 of about 4,369 (201)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingIn satellite remote sensing imaging, factors such as optical axis shift, image plane jitter, movement of the target object, and Earth's rotation can induce image blur.
Zhidan Cai +4 more
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Sensors, 2020 Image deblurring has been a challenging ill-posed problem in computer vision. Gaussian blur is a common model for image and signal degradation. The deep learning-based deblurring methods have attracted much attention due to their advantages over the ...
Quan Zhou, Mingyue Ding, Xuming Zhang
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Computation, 2021 The aim of the present paper is to improve an existing blind image deblurring algorithm, based on an independent component learning paradigm, by manifold calculus.
Simone Fiori
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Light Field Blind Motion Deblurring
, 2017 We study the problem of deblurring light fields of general 3D scenes captured under 3D camera motion and present both theoretical and practical contributions.
Ng, Ren +2 more
core +1 more source
ESFFA: Early‐Stage Feature Frequency Attack in Cross‐Domain Few‐Shot Learning
IET Computer Vision, Volume 20, Issue 1, January/December 2026.This paper addresses the challenge of cross‐domain few‐shot learning (CD‐FSL), where models often rely on frequency shortcuts rather than semantic features. We propose ESFFA (Early‐Stage Feature Frequency Attack), a novel method that perturbs low‐frequency statistics and masks high‐frequency components in shallow feature maps to reduce shortcut ...
Xu Wang +4 more
wiley +1 more source
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
Enhancing convolutional neural network generalizability via low‐rank weight approximation
IET Image Processing, Volume 20, Issue 1, January/December 2026.A self‐supervised framework is proposed for image denoising based on the Tucker low‐rank tensor approximation. With the proposed design, we are able to characterize our denoiser with fewer parameters and train it based on a single image, which considerably improves the model's generalizability and reduces the cost of data acquisition. Abstract Noise is
Chenyin Gao, Shu Yang, Anru R. Zhang
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Blind UAV Images Deblurring Based on Discriminative Networks
Sensors, 2018 Unmanned aerial vehicles (UAVs) have become an important technology for acquiring high-resolution remote sensing images. Because most space optical imaging systems of UAVs work in environments affected by vibrations, the optical axis motion and image ...
Ruihua Wang +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
core +1 more source
Diffusion Models and Its Applications in Image Dehazing: A Survey
IET Image Processing, Volume 20, Issue 1, January/December 2026.1.This survey represents the first systematic and comprehensive overview of diffusion model‐based image dehazing, aiming to provide a valuable guide for future researchers and stimulate continued progress in this field. 2.We summarize relevant papers along with their corresponding code links and other resources for image dehazing and all‐in‐one image ...
Liangyu Zhu +6 more
wiley +1 more source