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Ill-posed problems in early vision
1988
Proceedings of the IEEE
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Specific topics in early vision and their regularization are then analyzed rigorously, characterizing existence, uniqueness, a n d stability o f solutions. ...
We review here the relevant mathematical results o n ill-posed a n d ill-conditioned problems a n d introduce the formal aspects of regularization theory in the linear a n d nonlinear case. ...
Section VI contains some results related to inverse nonlinear prob- In the second part we show that several approaches, recently proposed by many authors to solve problems of early vision, using smoothness ...
doi:10.1109/5.5962
fatcat:zrblexiofnb5njxgd6xksamd2y
Insect-based visual motion detection with contrast adaptation
2005
Infrared Technology and Applications XXXI
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Our approach accounts for the basic nonlinear and temporal bandpass characteristics of early vision, includes a simple model of motion adaptation as a form of contrast gain control, followed by a correlational ...
input signal amplitude due to the nonlinearity imposed by the logarithmic transformation in early vision. ...
doi:10.1117/12.609470
fatcat:wiyq3os3lrhflf2w6evvmj2c74
A One-Dimensional Analog VLSI Implementation for Nonlinear Real-Time Signal Preprocessing
2001
Real-time imaging
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R econstruction of given noisy data is an ill-posed problem and a computationally intensive task. Nonlinear regularization techniques are used to find a unique solution under certain constraints. ...
Results from applying the 1D chip to nonlinear smoothing of twodimensional image data will also be given correspondence. ...
Build upon Mead's fundamental research, Harris [3, 19] implemented nonlinear resistive networks for early vision tasks. ...
doi:10.1006/rtim.1999.0218
fatcat:dmesnsnrsfc2jhr7vgakd47cki
Recursive Deep Residual Learning for Single Image Dehazing
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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Such novel reformulation enables us to directly estimate a nonlinear mapping from input hazy images to output dehazed ones (i.e., bypassing the unnecessary step of transmission map estimation). ...
The dehazing-denoising analogy also motivates us to leverage the strategy of iterative regularization from denoising to dehazing -i.e., we propose to recursively feed the dehazed image back to the input ...
In previous approaches, Estimating A and t(x) are necessary steps for image dehazing; in this work, we propose to bypass them and take a direct approach of learning a nonlinear mapping from I(x) to J(x ...
doi:10.1109/cvprw.2018.00116
dblp:conf/cvpr/DuL18
fatcat:qhrdli2a7rbyzp6dxx4aup5iuu
Deep Learning for Image/Video Restoration and Super-resolution
2022
Foundations and Trends in Computer Graphics and Vision
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We can consider learned image/video restoration and SR as learning either a nonlinear regressive mapping from degraded to ideal images based on the universal approximation theorem, or a generative model ...
An important benefit of data-driven deep learning approaches to image processing is that neural models can be optimized for any differentiable loss function, including perceptual loss functions, leading ...
Early iterative regularization methods include nonlinear Landweber iterations, iterative back-projection, or projection onto convex sets (POCS) methods. ...
doi:10.1561/0600000100
fatcat:5keqxf3lingubhlgrptdpq42xy
Methods for Postprocessing in Single-Step Diffuse Optical Tomography
[chapter]
2008
Computer Vision
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Acknowledgments The authors would like to thank V. N. Ananijchuk, S. V. Kolchugin, V. M. Kryukov and G. N. Rykovanov for their considerable long-standing encouragement and support.
References ...
Preconditioned iterative regularization by truncating the iterations is an effective approach to accelerate the rate of convergence (Nagy et al., 2004) . ...
In this case a special approach to image extrapolation is needed (Konovalov et al., 2006c) . ...
doi:10.5772/6162
fatcat:gh22nobqefbo3baoa7zq2secty
Regularization operators for natural images based on nonlinear perception models
2006
IEEE Transactions on Image Processing
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Biological visual systems have evolved to capture these relations.We propose the use of this biological behavior to build regularization operators as an alternative to simple statistical models. ...
Image restoration requires some a priori knowledge of the solution. Some of the conventional regularization techniques are based on the estimation of the power spectrum density. ...
They would also like to thank Dr. G. Camps for useful discussions on AR models, Dr. J. Viru for his insight on natural images features, Prof. J. M. Artigas, Dr. A. B. Watson, Dr. A. Ahumada, and Dr. ...
doi:10.1109/tip.2005.860345
pmid:16435549
fatcat:4vjlgxyifbajtlageb34vz2kx4
Efficient visual system processing of spatial and luminance statistics in representational and non-representational art
2009
Human Vision and Electronic Imaging XIV
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We show empirically that elements of contemporary approaches to high-dynamic range tone-mapping-which are themselves deeply rooted in an understanding of early visual system coding-are present in the way ...
An efficient visual system could make a quick and reasonable guess as to the relationship of a given image to others (i.e., its context) by extracting these basic statistics early in the visual stream, ...
Van Gogh-and other painters-would appear to employ a representational approach that is similar to a modern HDR tone mapping strategy. ...
doi:10.1117/12.817185
dblp:conf/hvei/GrahamFR09
fatcat:y27z3ie2xze5tid6qp4zqebbdm
Neural system identification for large populations separating "what" and "where"
[article]
2018
arXiv
pre-print
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Here, we show that a major bottleneck for fitting convolutional neural networks (CNNs) to neural data is the estimation of the individual receptive field locations, a problem that has been scratched only ...
Our network scales well to thousands of neurons and short recordings and can be trained end-to-end. ...
Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. ...
arXiv:1711.02653v2
fatcat:ck5jtzg4knas7dyqitedaik64u
Scripta Qumranica Electronica (2016–2021)
2016
Hebrew Bible and Ancient Israel
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Nonlinear Static (Pushover) Analysis (POA) is a time saving and simple assessment procedure prosposed in Eurocode 8 (EC8). However, its reliability in designing structure still remains a question. ...
A B S T R A C T Soft storey building is popular due to the functional and aesthetic purpose, despite its weakness in resisting seismic excitation. ...
The modern approach to earthquake resistant design is an attempt to design/retrofit buildings with predictable seismic performance through detreminsitic/probabilistic approach. ...
doi:10.1628/186870316x14805961757430
fatcat:lpvksxfwafdoleo4k2opugbmui
Physically based adaptive preconditioning for early vision
1997
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Several problems in early vision have been formulated in the past in a regularization framework. These problems, when discretized, lead to large sparse linear systems. ...
The adaptation of the preconditioner to an early vision problem is achieved via the explicit use of the spectral characteristics of the regularization filter in conjunction with the data. ...
Application to Early Vision Problems The general method for constructing our adaptive preconditioner for the early vision problems formulated in a regularization framework was discussed in Section 4. ...
doi:10.1109/34.601247
fatcat:cvoxdrzel5b53jp4cgdwcqfp6e
A new energy minimization framework and sparse linear system for path planning and shape from shading
2014
Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing - ICVGIP '14
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The limiting behavior, for a particular case, of this linear differential equation can be shown to converge to the nonlinear eikonal. ...
advantages of a linear systems approach. ...
However, lost in this flurry of advancing nonlinear solvers was a completely alternative approach, one which allows you to rigorously approximate solutions to the nonlinear eikonal by instead solving a ...
doi:10.1145/2683483.2683498
dblp:conf/icvgip/PeterGMR14
fatcat:c47dmqufxva4plafi5ljko4o5u
Radon Transform based Modified Nonlinear Access for Segmentation of Mammogram Application
2019
International journal of recent technology and engineering
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The proposed approach of nonlinear method of segmentation for which specific images of mammogram are consideredusing probability weighted force stopping function and Bayesian rules to extract the weak ...
In this paper a novel and application oriented mammogram segmentation using Nonlinear level set method and Radon Transform proposed. ...
CONCLUSION AND DISCUSSION This article construct novel approach of nonlinear with stopping force function based on probability weightedtoresolves problems which counter in early section. ...
doi:10.35940/ijrte.b1094.078219
fatcat:jrokk4fh3nd5hotdorjcd5uypi
Neural Encoding for Human Visual Cortex with Deep Neural Networks Learning "What" and "Where"
[article]
2019
bioRxiv
pre-print
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AbstractNeural encoding, a crucial aspect to understand human brain information processing system, aims to establish a quantitative relationship between the stimuli and the evoked brain activities. ...
The two forms of regularizations: sparsity and smoothness, are also adopted in our modeling approach, so that the receptive field can be estimated automatically without prior assumptions about shapes. ...
This modeling approach (Fig 1) of neural 7 encoding links fMRI signals at the millimeter scale to neural response at the micron scale, 8 providing a non-invasive approach to revealing the nonlinear ...
doi:10.1101/861989
fatcat:ow4llnj4mray5ig2lmjcs5zwnu
Statistical regularities of art images and natural scenes: Spectra, sparseness and nonlinearities
2007
Spatial Vision
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Because artists must produce images that can be seen by a visual system that is thought to take advantage of statistical regularities in natural scenes, artists are likely to replicate many of these regularities ...
But when a compressive nonlinearity was applied to the images, both the paintings' sparseness and the modeled responses to the paintings showed the same or greater sparseness compared to the natural scenes ...
We wish to acknowledge the many current and former staff of the H. F. ...
doi:10.1163/156856807782753877
pmid:18073056
fatcat:63k4zwwcq5hp7cfefbxgwrok2e
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