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Communication Dans Un Congrès Année : 2017

BLIND IMAGE QUALITY ASSESSMENT IN THE COMPLEX FREQUENCY DOMAIN

Résumé

In this paper, we propose a no-reference (NR) image quality assess- ment (IQA) metric that operates in the complex frequency domain. A set of features are developed to model the natural scene statistics without depending on any specific visual distortion. The proposed approach relies on a statistical analysis of the transformed image, involving the importance of the phase and magnitude provided by the underlying complex coefficients. We further investigate the cor- relation between the different image spatial-frequency resolutions, i.e., representations under different scales and orientations in order to extract the directional features and energy distributions of an im- age. The validation of the NR metric is performed on a variety of challenging IQA databases and the obtained results show good cor- relation with subjective scores. Besides, the obtained performance is highly competitive compared to the top-performing NR IQA met- rics.
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Dates et versions

hal-01629770 , version 1 (06-11-2017)

Identifiants

  • HAL Id : hal-01629770 , version 1

Citer

Kais Rouis, Mohamed-Chaker Larabi, Jamal Belhadj Tahar. BLIND IMAGE QUALITY ASSESSMENT IN THE COMPLEX FREQUENCY DOMAIN. IEEE International Conference on Image Processing (ICIP), Sep 2017, Beijing, China. ⟨hal-01629770⟩
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