Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
I3D '01 Proceedings of the 2001 symposium on Interactive 3D graphics
Real-time texture synthesis by patch-based sampling
ACM Transactions on Graphics (TOG)
Graphcut textures: image and video synthesis using graph cuts
ACM SIGGRAPH 2003 Papers
Feature matching and deformation for texture synthesis
ACM SIGGRAPH 2004 Papers
Patch-Based Texture Synthesis Using Wavelets
SIBGRAPI '05 Proceedings of the XVIII Brazilian Symposium on Computer Graphics and Image Processing
A fast nonparametric noncausal MRF-based texture synthesis scheme using a novel FKDE algorithm
IEEE Transactions on Image Processing
Texture synthesis via a noncausal nonparametric multiscale Markov random field
IEEE Transactions on Image Processing
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In this paper we propose a new theory for the order estimation of nonparametric Markov random field (N-MRF) model. Texture synthesis based on N-MRF model performs well visually for a wide range of natural textures, [9]. The result of texture synthesis is dependent upon the model order, and the computational complexity increases parabolicaly with the model order. Therefore, it is required to estimate the minimum model order for computationally efficient texture synthesis. In the proposed methodology, the basic definition of local conditional density is redefined. The proposed model order estimation (MOE) approach for N-MRF model has been tested with a number of stochastic and near-regular textures, collected from the Brodatz's standard database [3]. Results show the efficacy of the proposed approach in solving the MOE problem efficiently.