Textures synthesis-by-analysis based on a multiscale early-vision model

Abstract

This paper introduces a new texture synthesis-by-analysis method, applying a visual-based approach which has some important advantages over more traditional texture modeling and synthesis techniques. The basis of the method is to encode the textural information by sampling both the power spectrum and the histogram of homogeneously textured images. The spectrum is sampled in a log-polar grid by using a pyramid Gabor scheme. The input image is split into a set of 16 Gabor channels (using four spatial frequency levels and four orientations), plus a low-pass residual (LPR). The energy and equivalent bandwidths of each channel, as well as the LPR power spectrum and the histogram, are measured and the latter two are compressed. The synthesis process consists of generating 16 Gabor filtered independent noise signals with spectral centers equal to those of the Gabor filters, whose energy and equivalent bandwidths are calculated in order to reproduce the measured values. These band-pass signals are mixed into a single image, whose LPR power spectrum and histogram are modified to match the original features. Despite the coarse sampling scheme used, very good results have been achieved with non structured textures as well as with some quasi-periodic textures. Besides being applicable to a wide range of textures, the method is robust (stable, fully automatic, linear, and with a fixed code length) and compact (it uses only 69 parameters).