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Texture synthesis / Probability theory / Segmentation / Random field / Markov random field / Texture mapping / Kernel density estimation / Density estimation / Texture / Statistics / Non-parametric statistics / 3D computer graphics


Texture Synthesis via a Non-parametric Markov Random Field Rupert Paget and Dennis Longstaff Department of Electrical and Computer Engineering, University of Queensland, and the Cooperative Research Centre for Sensor, Si
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Document Date: 2009-01-20 17:55:14


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City

London / New York / /

Company

Dover Publications Inc. / /

Facility

Stanford Reseach Institute / University of Queensland / /

IndustryTerm

neighbourhood systems / energy function / texture synthesis algorithm / lattice systems / energy es / large neighbourhood systems / image processing / deterministic relaxation algorithm / synthesis algorithm / imaging / energy / /

Organization

Royal Statistical Society / Stanford Reseach Institute / vol. / International Congress / University of Queensland / Non-parametric Markov Random Field Rupert Paget and Dennis Longstaff Department of Electrical and Computer Engineering / Cooperative Research Centre for Sensor / Pattern Analysis and Machine Intelligence / /

Person

Ping Dong / Christine Graffigne / Donald Geman / Richard O. Duda / Julian E. Besag / Anil K. Jain / Richard C. Dubes / Peter E. Hart / Stuart Geman / Dennis Longstaff / /

Position

representative / Statistician / vol / /

ProvinceOrState

Queensland / California / New York / /

PublishedMedium

IEEE Transactions on Pattern Analysis and Machine Intelligence / Journal of the Royal Statistical Society / /

Technology

Two well known SR algorithms / image compression / deterministic relaxation algorithm / multiscale ICM texture synthesis algorithm / synthesis algorithm / ICM algorithm / image processing / PDF / Metropolis algorithm / /

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