Random phase fields and Gaussian fields for image sharpness assessment and fast texture synthesis

Procedural noises based on power spectrum definition and random phases have been widely used for procedural texturing, but using a noise process with random phases limits the types

We propose to extend the kernel definition of LCSN to model shell textures, i.e. We do this by defining fil- tered 3D kernels instead of 2D kernels and by projecting random

Co-occurrence matrices can describe a texture in terms of its statistics. A co- occurrence matrix can be viewed as a generalized/abstract form of a two

Abstract: Relying on the results of Chapter 7 and Chapter 8, the variation intensities of various stationary random field (r.f.) models are computed. In order of presentation,

The purpose of the Texture Cache component is to handle storage of needed tiles for the current rendering and to implement a least recently used (LRU) cache of tile data.. Since we

In the paper by Jojic, Frey and Kannan[42], when the epitomic representation is used within a hierarchical generative model, appropriate inference algorithms can be derived to

For estimating the Hurst parameter of ARFBF model, we provide two estimation methods based on Wavelet Packet (WP) spectrum [10]: the Log-Regression on Diagonal

The main contributions are (i) A new and versatile framework for image synthesis from a single example using multi-scale patch statistics and optimal transport; (ii) The computation