Results 271 to 280 of about 153,211 (306)
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Journal of Statistical Planning and Inference, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chan, A., Meloche, J.
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chan, A., Meloche, J.
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1994
We analyse a class of random fields invariant by stochastic synchronous updating of all sites, subject to a generalized reversibility assumption. We give a formal definition and properties of the model, study the problem of posterior simulation, parameter estimation, and then present experimental results in image restoration.
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We analyse a class of random fields invariant by stochastic synchronous updating of all sites, subject to a generalized reversibility assumption. We give a formal definition and properties of the model, study the problem of posterior simulation, parameter estimation, and then present experimental results in image restoration.
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Image enhancement and restoration
1975The aim of collecting data is to gain meaningful information about a phenomenon of interest. Unfortunately, often the phenomenon is not a direct physical observable. Instead, e.g., the data at hand may be a linear superposition of the desired quantities.
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Space-Variant Image Restoration
1997Publisher Summary This chapter offers information on space-variant image restoration. The inhomogeneity assumption introduced in this chapter allows the edges to be directly taken into account by the image model. A stochastic image-generating process is so obtained describing the gray level discontinuities by a space-varying model, where only the ...
De Santis, GERMANI, Alfredo, Jetto L.
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Digital image restoration: A survey
Computer, 1974The state of the art in large-scale digital computers has recently opened the way for high resolution image processing by digital techniques. With the increasing availability of digital image input/output devices it is becoming quite feasible for the average computing facility to embark upon high-quality image restoration and enhancement.
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General restoration filter for vibrated-image restoration
Applied Optics, 1998Mechanical vibrations are often the principal cause of image degradation. Low temporal-frequency mechanical vibrations involve random image degradation that depends on the instant of exposure. Exact restoration requires the calculation of a specific filter unique to each vibrated image.
A, Stern, N S, Kopeika
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Plug-and-Play Image Restoration With Deep Denoiser Prior
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022Kai Zhang, Yawei Li, Wangmeng Zuo
exaly
Learning Enriched Features for Fast Image Restoration and Enhancement
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023Syed Waqas Zamir +2 more
exaly
Conference on Colour in Graphics, Imaging, and Vision, 2002
Samir Belfkih, Philippe Montesinos
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Samir Belfkih, Philippe Montesinos
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A survey of deep learning approaches to image restoration
Neurocomputing, 2022Jingwen Su, Boyan Xu, Hujun Yin
exaly

