Abstract
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.
| Original language | English |
|---|---|
| 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 |
|---|---|
| Number | Part 2 |
| Volume | 1395 |
| ISSN | 0277-786X |
Fingerprint Dive into the research topics of 'Modified Markov random field model and its applications to texture synthesis and data compression'. Together they form a unique fingerprint.
Cite this
Baozong, Y., Yu, X., & Yuan, B. (1990). Modified Markov random field model and its applications to texture synthesis and data compression. In Close-Range Photogrammetry Meets Machine Vision (pp. 1203-1209). Proceedings of SPIE, No. Part 2, Vol.. 1395 https://doi.org/10.1117/12.2294396