Motion Blurred Star Image Restoration Based on MEMS Gyroscope Aid and Blur Kernel Correction [PDF]
Sensors, 2018 Under dynamic conditions, motion blur is introduced to star images obtained by a star sensor. Motion blur affects the accuracy of the star centroid extraction and the identification of stars, further reducing the performance of the star sensor.
Shijie Zhang, Botian Zhou
exaly +5 more sources
Motion Blur Kernel Rendering Using an Inertial Sensor: Interpreting the Mechanism of a Thermal Detector. [PDF]
Sensors (Basel), 2022 Various types of motion blur are frequently observed in the images captured by sensors based on thermal and photon detectors. The difference in mechanisms between thermal and photon detectors directly results in different patterns of motion blur ...
Lee K, Ban Y, Kim C.
europepmc +3 more sources
Blur Kernel Estimation and Non-Blind Super-Resolution for Power Equipment Infrared Images by Compressed Sensing and Adaptive Regularization. [PDF]
Sensors (Basel), 2021 Infrared sensing technology is more and more widely used in the construction of power Internet of Things. However, due to cost constraints, it is difficult to achieve the large-scale installation of high-precision infrared sensors.
Zhao H, Liu B, Wang L.
europepmc +3 more sources
Lightweight Implicit Blur Kernel Estimation Network for Blind Image Super-Resolution [PDF]
Information (Switzerland), 2023 Blind image super-resolution (Blind-SR) is the process of leveraging a low-resolution (LR) image, with unknown degradation, to generate its high-resolution (HR) version.
Niki Martinel +2 more
exaly +5 more sources
Applied Sciences (Switzerland), 2020 Image blurs are a major source of degradation in an imaging system. There are various blur types, such as motion blur and defocus blur, which reduce image quality significantly.
Haoyuan Yang, Xiuqin Su
exaly +4 more sources
Multiregression spatially variant blur kernel estimation based on inter‐kernel consistency
Electronics Letters, 2023 Most single‐image super‐resolution (SR) models suffer from the degradation of image restoration performance when restoring a high‐resolution (HR) image from a low‐resolution (LR) image downscaled using an unknown blur kernel. The spatially invariant blur
Min Hyuk Kim +2 more
doaj +2 more sources
Blur Unblurred—A Mini Tutorial [PDF]
i-Perception, 2018 Optical blur from defocus is quite frequently considered as equivalent to low-pass filtering. Yet that belief, although not entirely wrong, is inaccurate.
Hans Strasburger +2 more
doaj +2 more sources
Blur Kernel Estimation by Structure Sparse Prior
Applied Sciences, 2020 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.
Xiaobin Yuan, Jingping Zhu, Xiaobin Li
doaj +2 more sources
Multi-Frame Blind Super-Resolution Based on Joint Motion Estimation and Blur Kernel Estimation
Applied Sciences, 2022 Multi-frame super-resolution makes up for the deficiency of sensor hardware and significantly improves image resolution by using the information of inter-frame and intra-frame images.
Shanshan Liu +2 more
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IMAGE SHARPENING WITH BLUR MAP ESTIMATION USING CONVOLUTIONAL NEURAL NETWORK [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 We propose a method for choosing optimal values of the parameters of image sharpening algorithm for out-of-focus blur based on grid warping approach. The idea of the considered sharpening algorithm is to move pixels from the edge neighborhood towards the
A. Nasonov, A. Krylov, D. Lyukov
doaj +3 more sources