An evaluation of stochastic models for analysis and synthesis of gray-scale texture
Pattern Recognition Letters
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
Image quilting for texture synthesis and transfer
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Watermarking on CNN-UM for image and video authentication: Research Articles
International Journal of Circuit Theory and Applications
International Journal of Circuit Theory and Applications
Complex dynamics in one-dimensional CNNs: Research Articles
International Journal of Circuit Theory and Applications - Special Issue on CNN Technology (Part 1)
An eight layer cellular neural network for spatio-temporal image filtering: Research Articles
International Journal of Circuit Theory and Applications - Special Issue on CNN Technology (Part 1)
International Journal of Circuit Theory and Applications
Circuits, computers, and beyond Boolean logic: Research Articles
International Journal of Circuit Theory and Applications - Reviews in Circuits and Systems: On the Occasion of the 70th Birthday of J. O. Scanlan
On global exponential stability of standard and full-range CNNs
International Journal of Circuit Theory and Applications - Cellular Wave Computing Architecture
Cellular wave computer algorithms with spatial semantic embedding for handwritten text recognition
International Journal of Circuit Theory and Applications
A unified texture model based on a 2-D Wold-like decomposition
IEEE Transactions on Signal Processing
Texture synthesis via a noncausal nonparametric multiscale Markov random field
IEEE Transactions on Image Processing
Texture synthesis: textons revisited
IEEE Transactions on Image Processing
A bio-inspired two-layer mixed-signal flexible programmable chip for early vision
IEEE Transactions on Neural Networks
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The presented paper introduces a novel approach to patch-based texture synthesis. The proposed method utilizes Cellular Neural Networks (CNNs) for patch stitching, the most important operation of the synthesis procedure, expected to transform a patchwork made up of pieces of some small texture sample into a seamless, large texture. To fill in between-patch gaps, spontaneous pattern formation capabilities of CNNs are used. By using autoregressive filtering framework, we show that CNNs can be designed to generate complex stochastic fields that approximate stochastic and near-stochastic textures. The proposed texture-synthesis procedure is the following. After creating a patchwork from randomly drawn pieces of a small target texture, we fix boundary CNN conditions to edge pixels of all patches subject to stitching and execute an appropriately derived texture-approximating template. Finally, brightness of the resulting patterns is locally adjusted by executing a diffusion CNN template. As both processing steps involve pure CNN dynamics, the proposed patch-stitching method can be extremely fast if implemented in existing hardware (at the order of milliseconds for synthesizing several megapixel images). Copyright © 2012 John Wiley & Sons, Ltd.