IEEE Trans Image Process - Huber fractal image coding based on a fitting plane.

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Resumo

Recently, there has been significant interest in robust fractal image coding for the purpose of robustness against outliers. However, the known robust fractal coding methods (HFIC and LAD-FIC, etc.) are not optimal, since, besides the high computational cost, they use the corrupted domain block as the independent variable in the robust regression model, which may adversely affect the robust estimator to calculate the fractal parameters (depending on the noise level). This paper presents a Huber fitting plane-based fractal image coding (HFPFIC) method. This method builds Huber fitting planes (HFPs) for the domain and range blocks, respectively, ensuring the use of an uncorrupted independent variable in the robust model. On this basis, a new matching error function is introduced to robustly evaluate the best scaling factor. Meanwhile, a median absolute deviation (MAD) about the median decomposition criterion is proposed to achieve fast adaptive quadtree partitioning for the image corrupted by salt & pepper noise. In order to reduce computational cost, the no-search method is applied to speedup the encoding process. Experimental results show that the proposed HFPFIC can yield superior performance over conventional robust fractal image coding methods in encoding speed and the quality of the restored image. Furthermore, the no-search method can significantly reduce encoding time and achieve less than 2.0 s for the HFPFIC with acceptable image quality degradation. In addition, we show that, combined with the MAD decomposition scheme, the HFP technique used as a robust method can further reduce the encoding time while maintaining image quality.

Resumo Limpo

recent signific interest robust fractal imag code purpos robust outlier howev known robust fractal code method hfic ladfic etc optim sinc besid high comput cost use corrupt domain block independ variabl robust regress model may advers affect robust estim calcul fractal paramet depend nois level paper present huber fit planebas fractal imag code hfpfic method method build huber fit plane hfps domain rang block respect ensur use uncorrupt independ variabl robust model basi new match error function introduc robust evalu best scale factor meanwhil median absolut deviat mad median decomposit criterion propos achiev fast adapt quadtre partit imag corrupt salt pepper nois order reduc comput cost nosearch method appli speedup encod process experiment result show propos hfpfic can yield superior perform convent robust fractal imag code method encod speed qualiti restor imag furthermor nosearch method can signific reduc encod time achiev less s hfpfic accept imag qualiti degrad addit show combin mad decomposit scheme hfp techniqu use robust method can reduc encod time maintain imag qualiti

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