Reduced Complexity Rotation Invariant Texture Classification Using a Blind Deconvolution Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Blind image deblurring driven by nonlinear processing in the edge domain
EURASIP Journal on Applied Signal Processing
Wavelet-based modeling of singular values for image texture classification
Machine Graphics & Vision International Journal
Advanced film grain noise extraction and synthesis for high-definition video coding
IEEE Transactions on Circuits and Systems for Video Technology
Semiblind bussgang equalization for sparse channels
IEEE Transactions on Signal Processing
A fast nonparametric noncausal MRF-based texture synthesis scheme using a novel FKDE algorithm
IEEE Transactions on Image Processing
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In this paper, an unsupervised model-based texture reproduction technique is described. In accordance with the Julesz's (1962) conjecture, the statistical properties of the prototype up to the second order are copied in order to generate a synthetic texture perceptually indistinguishable from the given sample. However, this task is accomplished using a hybrid approach which operates partially in the spatial domain and partially in a multiresolution domain. The latter employed is the circular harmonic function (CHF) domain since it has been proven to be well suited for mimicking the behavior of the human visual system (HVS). This approach allows, for a wide range of textures typologies, obtaining synthetic textures that better match the prototype with respect to the ones obtained using techniques based on the Julesz's conjecture operating only in the spatial domain, and to dramatically reduce the computational complexity of similar methods operating only in the multiresolution domain