A fast nonparametric noncausal MRF-based texture synthesis scheme using a novel FKDE algorithm
IEEE Transactions on Image Processing
Nonparametric Markov random field order estimation and its application in texture synthesis
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
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Patch-based texture synthesis builds a texture by joining together blocks of pixels — patches — of the original sample. Usually the best patches are selected among all possible using a L2 norm on the RGB or grayscale pixel values of boundary zones. The L2 metric provides the raw pixel-to-pixel difference, disregarding relevant image structures — such as edges — that are relevant in the human visual system and therefore on synthesis of new textures. We present a wavelet-based approach for selecting patches for patch-based texture synthesis. For each possible patch we compute the wavelet coefficients for the boundary region and pick the patch with the smallest error computed from the wavelet coefficients. We show that the use of wavelets as metric for selection of the best patches improves texture synthesis for samples which previous work fails, mainly textures with prominent aligned features.