@article { , title = {A perceptually relevant approach to ringing region detection}, abstract = {An efficient approach toward a no-reference ringing metric intrinsically exists of two steps: first detecting regions in an image where ringing might occur, and second quantifying the ringing annoyance in these regions. This paper presents a novel approach toward the first step: the automatic detection of regions visually impaired by ringing artifacts in compressed images. It is a no-reference approach, taking into account the specific physical structure of ringing artifacts combined with properties of the human visual system (HVS). To maintain low complexity for real-time applications, the proposed approach adopts a perceptually relevant edge detector to capture regions in the image susceptible to ringing, and a simple yet efficient model of visual masking to determine ringing visibility. The approach is validated with the results of a psychovisual experiment, and its performance is compared to existing alternatives in literature for ringing region detection. Experimental results show that our method is promising in terms of both reliability and computational efficiency. © 2010 IEEE.}, doi = {10.1109/tip.2010.2041406}, eissn = {1941-0042}, issn = {1941-0042}, issue = {6}, journal = {IEEE transactions on image processing : a publication of the IEEE Signal Processing Society}, pages = {1414-1426}, publicationstatus = {Published}, publisher = {Institute of Electrical and Electronics Engineers}, url = {https://hull-repository.worktribe.com/output/467057}, volume = {19}, keyword = {Specialist Research - Other, Luminance masking, Perceptual edge, Ringing artifact, Texture masking}, year = {2010}, author = {Liu, Hantao and Klomp, Nick and Heynderickx, Ingrid} }