Pyramid-based texture analysis/synthesis
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Minimax entropy principle and its application to texture modeling
Neural Computation
Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
I3D '01 Proceedings of the 2001 symposium on Interactive 3D graphics
Applied Numerical Methods for Engineers Using MATLAB
Applied Numerical Methods for Engineers Using MATLAB
Principal Direction Divisive Partitioning
Data Mining and Knowledge Discovery
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Graphcut textures: image and video synthesis using graph cuts
ACM SIGGRAPH 2003 Papers
Improved Fast Gauss Transform and Efficient Kernel Density Estimation
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Feature matching and deformation for texture synthesis
ACM SIGGRAPH 2004 Papers
Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Genetic-Based EM Algorithm for Learning Gaussian Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Patch-Based Texture Synthesis Using Wavelets
SIBGRAPI '05 Proceedings of the XVIII Brazilian Symposium on Computer Graphics and Image Processing
Fast principal component analysis using fixed-point algorithm
Pattern Recognition Letters
VoCS'08 Proceedings of the 2008 international conference on Visions of Computer Science: BCS International Academic Conference
Texture synthesis via a noncausal nonparametric multiscale Markov random field
IEEE Transactions on Image Processing
Texture synthesis-by-analysis with hard-limited Gaussian processes
IEEE Transactions on Image Processing
A wavelet-based multiresolution statistical model for texture
IEEE Transactions on Image Processing
2-D moving average models for texture synthesis and analysis
IEEE Transactions on Image Processing
A multiresolution approach for texture synthesis using the circular harmonic functions
IEEE Transactions on Image Processing
Texture synthesis: textons revisited
IEEE Transactions on Image Processing
Nonparametric Markov random field order estimation and its application in texture synthesis
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Bilateral Markov mesh random field and its application to image restoration
Journal of Visual Communication and Image Representation
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In this paper, a new algorithm is proposed for fast kernel density estimation (FKDE), based on principal direction divisive partitioning (PDDP) of the data space. A new framework is also developed to apply FKDE algorithms (both proposed and existing), within nonparametric noncausal Markov random field (NNMRF) based texture synthesis algorithm. The goal of the proposed FKDE algorithm is to use the finite support property of kernels for fast estimation of density. It has been shown that hyperplane boundaries for partitioning the data space and principal component vectors of the data space are two requirements for efficient FKDE. The proposed algorithm is compared with the earlier algorithms, with a number of high-dimensional data sets. The error and time complexity analysis, proves the efficiency of the proposed FKDE algorithm compared to the earlier algorithms. Due to the local simulated annealing, direct incorporation of the FKDE algorithms within the NNMRF-based texture synthesis algorithm, is not possible. This work proposes a new methodology to incorporate the effect of local simulated annealing within the FKDE framework. Afterward, the developed texture synthesis algorithms have been tested with a number of different natural textures, taken from a standard database. The comparison in terms of visual similarity and time complexity, between the proposed FKDE based texture synthesis algorithm with the earlier algorithms, show the efficiency.