Results 161 to 170 of about 15,547 (189)
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Deblurring Signal Network Dynamics
ACS Chemical Biology, 2017To orchestrate the function and development of multicellular organisms, cells integrate intra- and extracellular information. This information is processed via signal networks in space and time, steering dynamic changes in cellular structure and function. Defects in those signal networks can lead to developmental disorders or cancer.
Dominic Kamps, Leif Dehmelt
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2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
We present a novel approach to noise-blind deblurring, the problem of deblurring an image with known blur, but unknown noise level. We introduce an efficient and robust solution based on a Bayesian framework using a smooth generalization of the 0-1 loss. A novel bound allows the calculation of very high-dimensional integrals in closed form.
Meiguang Jin, Stefan Roth, Paolo Favaro
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We present a novel approach to noise-blind deblurring, the problem of deblurring an image with known blur, but unknown noise level. We introduce an efficient and robust solution based on a Bayesian framework using a smooth generalization of the 0-1 loss. A novel bound allows the calculation of very high-dimensional integrals in closed form.
Meiguang Jin, Stefan Roth, Paolo Favaro
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Plenoptic Image Motion Deblurring
IEEE Transactions on Image Processing, 2018We propose a method to remove motion blur in a single light field captured with a moving plenoptic camera. Since motion is unknown, we resort to a blind deconvolution formulation, where one aims to identify both the blur point spread function and the latent sharp image.
Paramanand Chandramouli +3 more
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Motion-based motion deblurring
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004Motion blur due to camera motion can significantly degrade the quality of an image. Since the path of the camera motion can be arbitrary, deblurring of motion blurred images is a hard problem. Previous methods to deal with this problem have included blind restoration of motion blurred images, optical correction using stabilized lenses, and special cmos
Moshe, Ben-Ezra, Shree K, Nayar
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2014
A comprehensive guide to restoring images degraded by motion blur, bridging the traditional approaches and emerging computational photography-based techniques, and bringing together a wide range of methods emerging from basic theory as well as cutting-edge research.
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A comprehensive guide to restoring images degraded by motion blur, bridging the traditional approaches and emerging computational photography-based techniques, and bringing together a wide range of methods emerging from basic theory as well as cutting-edge research.
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Multi-scale Deformable Deblurring Kernel Prediction for Dynamic Scene Deblurring
2021Deblurring aims to restore clear images from blurred ones. Recently deep learning are widely used. Previous methods regard deblurring as dense prediction problems and rarely consider the inverse operation of blur. In this paper, we propose a multi-scale deformable deblurring kernel prediction network for dynamic scene deblurring which uses a coarse-to ...
Kai Zhu, Nong Sang
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IEEE Transactions on Acoustics, Speech, and Signal Processing, 1987
We introduce a modified Backus-Gilbert technique for restoring an image that has been distorted by a linear system whose impulse response function is itself random, and in the presence of detection noise. The restoration is based on a weighted superposition of a small number of shifted versions of the distorted image.
R. Ward, B. Saleh
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We introduce a modified Backus-Gilbert technique for restoring an image that has been distorted by a linear system whose impulse response function is itself random, and in the presence of detection noise. The restoration is based on a weighted superposition of a small number of shifted versions of the distorted image.
R. Ward, B. Saleh
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2014
Recovering a sharp version of an input blurred image is challenging in computational photography and digital image processing. Recent progresses have been made in algorithms to address the ill-posedness of the problem. Yet, the results are imperfect. This thesis presents two approaches that explore latent priors from observations to provide a better ...
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Recovering a sharp version of an input blurred image is challenging in computational photography and digital image processing. Recent progresses have been made in algorithms to address the ill-posedness of the problem. Yet, the results are imperfect. This thesis presents two approaches that explore latent priors from observations to provide a better ...
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Deblurring random time-varying blur
Journal of the Optical Society of America A, 1989The problem of restoring a constant image distorted by a system of random time-varying point-spread functions is studied. The restoration is based on a finite number of images that are observed in a finite period of time. Two features distinguish this problem. The first is that of the signal-noise dependency, and the second is the availability of large
L, Guan, R K, Ward
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2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016
A histogram is an effective form for extracting various types of features and has been attracting keen attention in pattern recognition fields. In visual recognition, however, the histogram features suffer from smoothing due to the processes of quantizing continuous input patterns into discrete codes and pooling them.
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A histogram is an effective form for extracting various types of features and has been attracting keen attention in pattern recognition fields. In visual recognition, however, the histogram features suffer from smoothing due to the processes of quantizing continuous input patterns into discrete codes and pooling them.
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