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.
|Title of host publication||Close-Range Photogrammetry Meets Machine Vision|
|Publication status||Published - 1990|
|MoE publication type||A4 Article in a conference publication|
|Series||Proceedings of SPIE|
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