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Just noticeable defocus blur detection and estimation

Jianping Shi, Li Xu, Jiaya Jia
2015 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
We tackle a fundamental yet challenging problem to detect and estimate just noticeable blur (JNB) caused by defocus that spans a small number of pixels in images.  ...  It directly establishes correspondence between sparse edge representation and blur strength estimation. Extensive experiments manifest the generality and robustness of this feature.  ...  Different from traditional camera motion blur estimation [5, 27, 9, 26, 18] where blur is significant and anisotropic, just noticeable blur mainly deals with slight defocus blur.  ... 
doi:10.1109/cvpr.2015.7298665 dblp:conf/cvpr/ShiXJ15 fatcat:7hnxrmuv5rfmxppmlxrx5oytcu

Fast defocus map estimation

Ding-Jie Chen, Hwann-Tzong Chen, Long-Wen Chang
2016 2016 IEEE International Conference on Image Processing (ICIP)  
The experimental results show that our method is efficient and able to estimate a plausible superpixel-level defocus map from a given single image.  ...  Since the pixel-level propagation step is timeconsuming, we develop an effective method to obtain the whole-image defocus blur using oversegmentation and transductive inference.  ...  The blur scale of each pixel is then selected by a constrained pairwise energy function. Shi et al. [15] estimate the small defocus blur via the statistics of sparse just noticeable blur features.  ... 
doi:10.1109/icip.2016.7533103 dblp:conf/icip/ChenCC16 fatcat:ttivd4lpmndkrdvitcfls7efce

Minimum change in spherical aberration that can be perceived

Silvestre Manzanera, Pablo Artal
2016 Biomedical Optics Express  
Using a flicker detection-based procedure implemented on an adaptive optics visual simulator, we measured the spherical aberration thresholds that produce just-noticeable differences in perceived image  ...  The thresholds were measured for positive and negative values of spherical aberration, for best focus and + 0.5 D and + 1.0 D of defocus.  ...  Even considering the intrinsic subjective nature of the requested task for the subject, the detection of flicker may be easier than the detection of just-noticeable differences in a continuously slowly  ... 
doi:10.1364/boe.7.003471 pmid:27699113 pmcid:PMC5030025 fatcat:7dlhcseubfaxdkm2bqwotfcbzy

Defocus Blur Detection and Estimation from Imaging Sensors

2018 Sensors  
In this paper, an improved sparse representation based method is proposed to detect and estimate defocus blur of imaging sensors.  ...  Experimental results validate that the proposed method outperforms existing defocus blur estimation approaches, both qualitatively and quantitatively.  ...  [30] has recently proposed a just noticeable defocus blur detection (JNB) method.  ... 
doi:10.3390/s18041135 pmid:29642491 pmcid:PMC5949045 fatcat:hvu2lj6o2jfsnbia5vqvlxy3nm

Spatially variant defocus blur map estimation and deblurring from a single image

Xinxin Zhang, Ronggang Wang, Xiubao Jiang, Wenmin Wang, Wen Gao
2016 Journal of Visual Communication and Image Representation  
In this paper, we propose a single image deblurring algorithm to remove spatially variant defocus blur based on the estimated blur map.  ...  Finally, ringing artifacts and noises are detected and removed, to obtain a high quality in-focus image.  ...  [22] estimated the just noticeable blur (JNB) by the dictionary method.  ... 
doi:10.1016/j.jvcir.2016.01.002 fatcat:gu3ookpajzdcdlsp67to2wap3q

Defocus Discrimination in Video: Motion in Depth

Vincent A. Petrella, Simon Labute, Michael S. Langer, Paul G. Kry
2017 i-Perception  
The second experiment measures a viewer's ability to notice momentary defocus and shows that the threshold of blur detection in arc minutes decreases significantly as the duration of the blur increases  ...  We perform two psychophysics experiments to investigate a viewer's ability to detect defocus in video; in particular, the defocus that arises in video during motion in depth when the camera does not maintain  ...  We used a weighted 1-up/2-down method to estimate the detection threshold values.  ... 
doi:10.1177/2041669517737560 pmid:29201337 pmcid:PMC5700795 fatcat:4gditjvsiretzc6tph6mv7aqsq

Conceptual model of human blur perception

Kenneth J. Ciuffreda, Bin Wang, Balamurali Vasudevan
2007 Vision Research  
It incorporates the concepts of blur detection and blur discrimination in depth, and across the central and peripheral retina, in two-and three-dimensional visual space.  ...  defocus between the central and peripheral retina.  ...  David Wong and Mr. Trevor Irish for their help with the data collection, and Drs. RosenWeld, Kapoor, and Aquilante for clinical evaluation of the subjects.  ... 
doi:10.1016/j.visres.2006.12.001 pmid:17223154 fatcat:g7jyzl2yvbakfayszng7bc3lve

Defocus Deblurring Using Dual-Pixel Data [article]

Abdullah Abuolaim, Michael S. Brown
2020 arXiv   pre-print
Correcting defocus blur is challenging because the blur is spatially varying and difficult to estimate.  ...  Defocus blur arises in images that are captured with a shallow depth of field due to the use of a wide aperture.  ...  The views expressed are his own and do not necessarily represent the views of Samsung Research.  ... 
arXiv:2005.00305v3 fatcat:rkkbcmkj7rgkpfzrwanxwwc7ti

Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes

S. Alireza Golestaneh, Lina J. Karam
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Our approach computes blur detection maps based on a novel High-frequency multiscale Fusion and Sort Transform (HiFST) of gradient magnitudes.  ...  The detection of spatially-varying blur without having any information about the blur type is a challenging task.  ...  blurred and unblurred regions is still noticeable.  ... 
doi:10.1109/cvpr.2017.71 dblp:conf/cvpr/GolestanehK17 fatcat:rjzow5g7prbrrccmjkt7lowgla

Equiblur zones at the fovea and near retinal periphery

Bin Wang, Kenneth J. Ciuffreda, Trevor Irish
2006 Vision Research  
Both the group mean blur detection and successive blur discrimination thresholds progressively increased with retinal eccentricity.  ...  Knowledge regarding successive blur discrimination thresholds (i.e., equiblur zones) in depth and across the near retinal periphery, and their relation to blur detection (i.e., depth-of-focus), remains  ...  In contrast, blur discrimination refers to the allowable range of retinal defocus before an already blurry target appears to be just noticeably blurrier.  ... 
doi:10.1016/j.visres.2006.04.005 pmid:16750552 fatcat:eyn3pfiy3vhlxpcbzzttp3fjhe

Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes [article]

S. Alireza Golestaneh, Lina J. Karam
2017 arXiv   pre-print
Our approach computes blur detection maps based on a novel High-frequency multiscale Fusion and Sort Transform (HiFST) of gradient magnitudes.  ...  The detection of spatially-varying blur without having any information about the blur type is a challenging task.  ...  blurred and unblurred regions is still noticeable.  ... 
arXiv:1703.07478v3 fatcat:lkpcrxklefhwzbjmdkdvdlq3hu

Depth Estimation from Defocused Images: A Survey

Jyoti B. Kulkarni, C. M. SheelaRani
2018 International Journal of Advances in Applied Sciences  
This paper presents a survey of Depth Perception from Defocused or blurs images as well as image from motion.  ...  The amount of blurring will be calculated with a comparison in front of the camera directly and can be seen with the changes at gray level around the edges of objects.</p>  ...  focused image reconstruction using blur function magnitude estimation, (e) focused image reconstruction using blur function magnitude and phase estimation [Depth Estimation from Defocused Images: a Survey  ... 
doi:10.11591/ijaas.v7.i3.pp220-225 fatcat:4vilp7ss4bdorfsrrwsllze6v4

Estimation of the depth of focus from wavefront measurements

Fan Yi
2010 Journal of Vision  
Significant correlation was found between the subject's estimated threshold level and the HOA RMS (Pearson's r=0.88, p<0.001).  ...  In such methods, DOF is defined as the range of defocus error that degrades the retinal image quality calculated from IQMs to a certain level of the maximum value.  ...  The most frequently used criteria include decrease of visual acuity, perception of just detectable image blur, and loss of visibility of target details .  ... 
doi:10.1167/10.4.3 pmid:20465323 fatcat:336c2lsqn5b5dnep3oxn6zi7gi

Deep Defocus Map Estimation Using Domain Adaptation

Junyong Lee, Sungkil Lee, Sunghyun Cho, Seungyong Lee
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Our method is evaluated on publicly available blur detection and blur estimation datasets and the results show the state-of-the-art performance.  ...  In this paper, we propose the first end-to-end convolutional neural network (CNN) architecture, Defocus Map Estimation Network (DMENet), for spatially varying defocus map estimation.  ...  This work was supported by the Ministry of Science and ICT, Korea, through IITP grant (IITP-2015-0-00174) and NRF grants (NRF-2017M3C4A7066316, NRF-2017M3C4A7066317).  ... 
doi:10.1109/cvpr.2019.01250 dblp:conf/cvpr/LeeLCL19 fatcat:6svprfmkvremtbi3veueomisse

An Efficient Defocus Blur Segmentation Scheme Based on Hybrid LTP and PCNN

Sadia Basar, Abdul Waheed, Mushtaq Ali, Saleem Zahid, Mahdi Zareei, Rajesh Roshan Biswal
2022 Sensors  
and object detection or recognition in defocus-blur images.  ...  It is noticed that the extracted fusion of upper and lower patterns of proposed sharpness-measure yields more noticeable results in terms of regions and edges compared to referenced algorithms.  ...  [14] presented a new sparse-feature based technique for estimating the just noticeable blur in deblurred images.  ... 
doi:10.3390/s22072724 pmid:35408338 pmcid:PMC9003284 fatcat:csazpcv5oveltldtnivg6phroa
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