Blur Detection, Depth of Field, and Accommodation in Emmetropic and Hyperopic Children.
Sign Up to like & getrecommendations! Published in 2018 at "Optometry and Vision Science"
DOI: 10.1097/opx.0000000000001177
Abstract: SIGNIFICANCE Our results demonstrate that blur detection thresholds are elevated in young children compared with adults, and poorer blur detection thresholds are significantly correlated with the magnitude of accommodative microfluctuations. Given that accommodative microfluctuations are… read more here.
Keywords: detection; depth field; accommodative microfluctuations; detection thresholds ... See more keywords
Defocus Blur Detection by Fusing Multiscale Deep Features With Conv-LSTM
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2996200
Abstract: Defocus blur detection aiming at distinguishing out-of-focus blur and sharpness has attracted considerable attention in computer vision. The present blur detectors suffer from scale ambiguity, which results in blur boundaries and low accuracy in blur… read more here.
Keywords: defocus blur; blur detection; blur; multiscale deep ... See more keywords
Heterogeneous Attention Nested U-Shaped Network for Blur Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2021.3128375
Abstract: With the popularity of image sensors in various mobile devices, image blurring caused by hand shaking or out of focus becomes ubiquitous, which deteriorates image quality and poses challenges for vision tasks, including object detection,… read more here.
Keywords: blur detection; image; heterogeneous attention; detection ... See more keywords
MA-GANet: A Multi-Attention Generative Adversarial Network for Defocus Blur Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3171424
Abstract: Background clutters pose challenges to defocus blur detection. Existing approaches often produce artifact predictions in background areas with clutter and relatively low confident predictions in boundary areas. In this work, we tackle the above issues… read more here.
Keywords: blur detection; defocus blur; generative adversarial; detection ... See more keywords