Modified Markov random field model and its applications to texture synthesis and data compression

Xiaohan Yu

doi:10.1117/12.2294396

1 August 1990 Modified Markov random field model and its applications to texture synthesis and data compression

Xiaohan Yu

Proceedings Volume 1395, Close-Range Photogrammetry Meets Machine Vision; 139549 (1990) https://doi.org/10.1117/12.2294396
Event: Close-Range Photogrammetry Meets Machine Vision, 1990, Zurich, Switzerland

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.

Citation Download Citation

Xiaohan Yu "Modified Markov random field model and its applications to texture synthesis and data compression", Proc. SPIE 1395, Close-Range Photogrammetry Meets Machine Vision, 139549 (1 August 1990); https://doi.org/10.1117/12.2294396

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