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Article Dans Une Revue Signal, Image and Video Processing Année : 2012

Reduced reference image quality assessment based on statistics in empirical mode decomposition domain

Résumé

This paper deals with the image quality assessment (IQA) task using a natural image statistics approach. A reduced reference (RRIQA) measure based on the bidimensional empirical mode decomposition is introduced. First, we decompose both, reference and distorted images, into intrinsic mode functions (IMF) and then we use the generalized Gaussian density (GGD) to model IMF coefficients of the reference image. Finally, we measure the impairment of a distorted image by fitting error between the IMF coefficients histogram of the distorted image and the estimated IMF coefficients distribution of the reference image, using the Kullback-Leibler divergence (KLD). Furthermore, to predict the quality, we propose a new support vector machine-based (SVM) classification approach as an alternative to logistic function-based regression. In order to validate the proposed measure, three benchmark datasets are involved in our experiments. Results demonstrate that the proposed metric compare favorably with alternative solutions for a wide range of degradation encountered in practical situations.
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Dates et versions

hal-00960021 , version 1 (17-03-2014)

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Abdelkaher Ait Abdelouahad1,, Mohammed El Hassouni, Hocine Cherifi, Driss Aboutajdine. Reduced reference image quality assessment based on statistics in empirical mode decomposition domain. Signal, Image and Video Processing, 2012, pp.1-18. ⟨10.1007/s11760-012-0407-0⟩. ⟨hal-00960021⟩
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