Image quality assessment based on perceptual grouping - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of Southeast University (English Edition) Année : 2016

Image quality assessment based on perceptual grouping

Résumé

To further explore the human visual system(HVS), the perceptual grouping(PG), which has been proven to play an important role in the HVS, is adopted to design an effective image quality assessment(IQA)model. Compared with the existing fixed-window-based models, the proposed one is an adaptive window-like model that introduces the perceptual grouping strategy into the IQA model. It works as follows: first, it preprocesses the images by clustering similar pixels into a group to the greatest extent; then the structural similarity is used to compute the similarity of the superpixels between reference and distorted images; finally, it integrates all the similarity of superpixels of an image to yield a quality score. Experimental results on three databases(LIVE, IVC and MICT)show that the proposed method yields good performance in terms of correlation with human judgments of visual quality.
Fichier non déposé

Dates et versions

hal-01304695 , version 1 (21-04-2016)

Identifiants

Citer

Wang Tonghan, Lu Zhang, Huizhen Jia, Kong Youyong, Li Baosheng, et al.. Image quality assessment based on perceptual grouping. Journal of Southeast University (English Edition), 2016, 32 (1), pp.29-34. ⟨10.3969/j.issn.1003-7985.2016.01.006⟩. ⟨hal-01304695⟩
173 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More