Image quality assessment (IQA) has been important issue in image processing. While using subjective quality assessment for image processing algorithms is suitable, it is hard to get subjective quality because of time and money. A lot of objective quality assessment algorithms are used widely as a substitution. Objective quality assessment divided into three types based on existence of reference image : full-reference, reduced-reference, and no-reference IQA. No-reference IQA is more difficult than fullreference IQA because it does not have any reference image. In this paper, we propose a novel no-reference IQA algorithm to measures contrast of image. The proposed algorithm is based on just-noticeable-difference which utilizes the human visual system (HVS). Experimental results show the proposed method performs better than conventional no-reference IQAs.
Minsub Kim, Ki Sun Song, Moon Gi Kang, "No-reference image contrast assessment based on just-noticeable-difference" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Quality and System Performance XIV, 2017, pp 26 - 29, https://doi.org/10.2352/ISSN.2470-1173.2017.12.IQSP-221