Results 61 to 70 of about 4,369 (201)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingBlind deblurring of optical remote sensing images has been a longstanding challenge. In recent years, many learning-based deblurring algorithms have been greatly developed.
Zhiyuan Li +4 more
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Progressive deep network for blind motion image deblurring
Xi'an Gongcheng Daxue xuebao, 2023 The multi-stage deep neural network in the blind motion image deblurring task lacks a large range of receptive fields and it was difficult to reasonably interact with the image features of each stage.
WANG Xiaohua +4 more
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Learning to Deblur Images with Exemplars
, 2018 Human faces are one interesting object class with numerous applications. While significant progress has been made in the generic deblurring problem, existing methods are less effective for blurry face images.
Hu, Zhe +3 more
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Learning a Discriminative Prior for Blind Image Deblurring [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 This paper is accepted by CVPR2018 as ...
Lerenhan Li +5 more
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Semi-blind image deblurring based on framelet prior
Signal, Image and Video Processing, 2023 The problem of image blurring is one of the most studied topics in the field of image processing. Image blurring is caused by various factors such as hand or camera shake. To restore the blurred image, it is necessary to know information about the point spread function (PSF).
Mohammad Zarebnia, R. Parvaz
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Earth and Space Science, Volume 12, Issue 12, December 2025.Abstract X‐band Phased array radars are characterized by high spatial and temporal resolution, but suffer from a range of data quality problems, such as echo voids after the filtering of ground clutter, abnormal radials, radial obstructions and irregular missing radar echoes. This paper proposes a radar echo image restoration model (GCD) based on color
Jinyan Xu +6 more
wiley +1 more source
Single Image Defocus Deblurring Based on Structural Information Enhancement
IEEE AccessDefocus deblurring is an important task in computer vision that aims to bring images back to clarity. Over recent years, both blind defocuse deblurring and non-blind defocuse deblurring methods have made great progress in the single image defocus ...
Guangming Feng +3 more
doaj +1 more source
From Nano Robotic Manipulation to Nano Manipulation Robot
SmartBot, Volume 1, Issue 3, September 2025.This review addresses a critical research gap by summarizing advancements in nano robotic manipulation, tracing its evolution from passive observation to autonomous nanomanipulation robots. It explores the interplay of observation, construction, and operation, unveiling fundamental principles of atomic‐scale control. The review establishes a systematic
Zhan Yang +6 more
wiley +1 more source
Understanding Kernel Size in Blind Deconvolution
, 2019 Most blind deconvolution methods usually pre-define a large kernel size to guarantee the support domain. Blur kernel estimation error is likely to be introduced, yielding severe artifacts in deblurring results.
Ren, Dongwei, Si-Yao, Li, Yin, Qian
core +1 more source
Temperature‐Resilient Polymeric Memristors for Effective Deblurring in Static and Dynamic Imaging
Advanced Functional Materials, Volume 35, Issue 23, June 5, 2025.A thermally stable organic memristor based on a thiadiazolobenzotriazole (TBZ) and 2,5‐Dioctyl‐3,6‐di(thiophen‐2‐yl)pyrrolo[3,4‐c]pyrrole‐1,4(2H,5H)‐dione (DPP)‐based conjugated polymer is presented, demonstrating reliable, gradual resistance switching across a wide temperature range (153–573 K).
Ziyu Lv +15 more
wiley +1 more source