Abstract
Original language | English |
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Title of host publication | Close-Range Photogrammetry Meets Machine Vision |
Pages | 1203-1209 |
DOIs | |
Publication status | Published - 1990 |
MoE publication type | A4 Article in a conference publication |
Publication series
Series | Proceedings of SPIE |
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Number | Part 2 |
Volume | 1395 |
ISSN | 0277-786X |
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Modified Markov random field model and its applications to texture synthesis and data compression. / Baozong, Yuan; Yu, Xiaohan; Yuan, Baozong.
Close-Range Photogrammetry Meets Machine Vision. 1990. p. 1203-1209 (Proceedings of SPIE; No. Part 2, Vol. 1395).Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
TY - GEN
T1 - Modified Markov random field model and its applications to texture synthesis and data compression
AU - Baozong, Yuan
AU - Yu, Xiaohan
AU - Yuan, Baozong
PY - 1990
Y1 - 1990
N2 - Markov Random Field (MRF) model is a very useful model for image texture processing. But its stability condition is hardly to meet for natural textures. To find a stable MRF model is difficult and complex in computation. In this paper a new MRF model, called Modified Markov Random Field Model, is proposed; A stable Modified MRF model can be easily obtained for stochastic and natural textures. It is suitable for texture synthesis and data compression.
AB - Markov Random Field (MRF) model is a very useful model for image texture processing. But its stability condition is hardly to meet for natural textures. To find a stable MRF model is difficult and complex in computation. In this paper a new MRF model, called Modified Markov Random Field Model, is proposed; A stable Modified MRF model can be easily obtained for stochastic and natural textures. It is suitable for texture synthesis and data compression.
U2 - 10.1117/12.2294396
DO - 10.1117/12.2294396
M3 - Conference article in proceedings
T3 - Proceedings of SPIE
SP - 1203
EP - 1209
BT - Close-Range Photogrammetry Meets Machine Vision
ER -