title: Monotonic regression: a new way for correlating subjective and objective ratings in image quality research.
abstract: To assess the performance of image quality metrics (IQMs), some regressions, such as logistic regression and polynomial regression, are used to correlate objective ratings with subjective scores. However, some defects in optimality are shown in these regressions. In this correspondence, monotonic regression (MR) is found to be an effective correlation method in the performance assessment of IQMs. Both theoretical analysis and experimental results have proven that MR performs better than any other regression. We believe that MR could be an effective tool for performance assessment in the IQM research.
authors: Yu
authors: Y
authors: Han
authors: Yunze
authors: Y
authors: Cai
authors: Yin
authors: Y
authors: Cao
authors: Xiaoming
authors: X
authors: Xu
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D013382:Subtraction Technique