A new structure tensor based image inpainting algorithm
by Ying Liu; Chanjuan Liu; Hailin Zou
International Journal of Grid and Utility Computing (IJGUC), Vol. 7, No. 4, 2016

Abstract: A new structure tensor based image inpainting algorithm (STIA) is proposed for solving the deficiencies of the classical Criminisi method, such as the error repair accumulation, high time complexity caused by the unreasonable design of the patch priority, inaccuracy criterion and its global search strategy. Firstly, considering the characteristic of the structure tensor in describing image structure, we make a combination between the structure tensor and the priority function to optimise the repair order of the damaged patches. And this new design idea increases the influence of structural information on repairing. Secondly, to lower the time complexity, an improved matching constraint equation and optimal matching criterion are presented using characteristic value of the structure tensor. Finally, damaged gray and colour images are tested respectively to verify the new algorithm. Experiments show that the improved algorithm not only maintains the structure and texture of images but also makes progress in both subjective visual effect and objective indexes compared with some of the typical image restoration algorithms proposed in recent years.

Online publication date: Thu, 15-Dec-2016

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