Reduced Complexity Rotation Invariant Texture Classification Using a Blind Deconvolution Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hi-index | 0.01 |
An unsupervised color texture synthesis-by analysis method is described. The texture is reproduced to appear perceptually similar to a given prototype by copying its statistical properties up to the second order. The synthesized texture is obtained at the output of a single-input three-output nonlinear system driven by a realization of a white Gaussian random field. Significant complexity reduction is gained by exploiting the rank deficiency of the cross power spectral density matrix of the color texture samples