Open AccessBlind image quality assessment based on fractal description of natural scenes
Author(s) -
Ding Yong,
Zhang Hang,
Luo Xiaohua,
Dai Hang
Publication year - 2015
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2014.2781
Subject(s) - fractal dimension , artificial intelligence , fractal , basis (linear algebra) , box counting , consistency (knowledge bases) , computer vision , dimension (graph theory) , image quality , pattern recognition (psychology) , image (mathematics) , computer science , scene statistics , fractal analysis , perception , mathematics , geometry , mathematical analysis , neuroscience , pure mathematics , biology
Motivated by the observation that visual perception is quite sensitive to the irregularities of natural scenes, the incorporation of the multi‐fractal spectrum and the fractal dimension into blind image quality assessment for perceptual features extraction is introduced. On the basis of a box‐counting method, the multi‐fractal spectrum and fractal dimension are extracted from natural scenes and then their discrepancies are quantified. Experiments on the LIVE image database show that consistency with subjective evaluation is achieved. In addition, these are remarkable advantages when compared with other popular methods are demonstrated.