RCBM: a rough content-based image quality assessment metric. (1st January 2013)

• Record Type: Journal Article
• Authors: Yu, Qian; Dong, Wei; Zhang, Chang N.
• Is Part Of: International journal of granular computing, rough sets and intelligent systems. Volume 3:Number 1(2013)
• Page Start: 44
• Page End: 58
• Publication Date: 2013-01-01
• Subjects: rough sets -- fuzzy measure -- rough fuzzy integral -- image quality assessment -- structural similarity; Intelligent agents (Computer science) -- Periodicals; 006.3
• Languages: English
• ISSNs: 1757-2703

Abstract

A generalised content-based image quality assessment technique is proposed in this paper. Different from many existing image quality metrics, where the digital image quality is evaluated by comparing with a reference image and a single 'exact' value is provided for the purpose of 'accurately' quantifying the image quality, our proposed method defines the image quality metric based on the theory of the rough fuzzy integral and a region (with a pair of the boundary values) is presented to estimate the image quality instead of a scalar value. The new philosophy for the proposed 'rough' content-based image quality metric lays on the acceptance of the uncertainty of subjective image quality assessment through the human visual system (HVS) and addresses this kind of uncertainty by applying the rigorous mathematical concept of the rough and fuzzy set on the standard content-based image quality analysis. Therefore, the proposed method is a good mimicking of the subjective image quality assessment and meets the accuracy requirement under the uncertainty measurement of HVS.