Blur Kernel Estimation and Non-Blind Super-Resolution for Power Equipment Infrared Images by Compressed Sensing and Adaptive Regularization [PDF]
Sensors, 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.
Hongshan Zhao +2 more
doaj +2 more sources
Robust Motion Blur Kernel Estimation by Kernel Continuity Prior [PDF]
IEEE Access, 2020 The accurate kernel estimation is key to the blind motion deblurring. Many previous methods depend on the image regularization to recover strong edges in the observed image for kernel estimation.
Xueling Chen +3 more
doaj +2 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 Kernel Estimation by Structure Sparse Prior [PDF]
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 +3 more sources
Quantitative Kernel estimation from traffic signs using slanted edge spatial frequency response as a sharpness metric [PDF]
Scientific ReportsSharpness is a critical optical property of automotive cameras, measured by the spatial frequency response (SFR) within the end-of-line (EOL) test after manufacturing.
Amit Pandey +4 more
doaj +2 more sources
Unsupervised Blur Kernel Estimation and Correction for Blind Super-Resolution
IEEE Access, 2022 Blind super-resolution (blind-SR) is an important task in the field of computer vision and has various applications in real-world. Blur kernel estimation is the main element of blind-SR along with the adaptive SR networks and a more accurately estimated ...
Youngsoo Kim +3 more
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
doaj +1 more source
Blind Text Image Deblurring Algorithm Based on Multi-Scale Fusion and Sparse Priors
IEEE Access, 2023 The goal of blind text image deblurring is to obtain a clean text image from the given blurry text image without knowing the blur kernel. Sparsity-based methods have been shown their effectiveness in various blind text image deblurring models.
Zhe Li +3 more
doaj +1 more source
Sensors, 2021 Infrared images of power equipment play an important role in power equipment status monitoring and fault identification. Aiming to resolve the problems of low resolution and insufficient clarity in the application of infrared images, we propose a blind ...
Yan Wang +3 more
doaj +1 more source
Pixel-Level Kernel Estimation for Blind Super-Resolution
IEEE Access, 2021 Throughout the past several years, deep learning-based models have achieved success in super-resolution (SR). The majority of these works assume that low-resolution (LR) images are ‘uniformly’ degraded from their corresponding high ...
Jaihyun Lew, Euiyeon Kim, Jae-Pil Heo
doaj +1 more source