Applications of Objective Image Quality Assessment Methods [Applications Corner]
Zhou Wang · IEEE Signal Processing Magazine · 2011
The interest in objective image quality assessment (IQA) has been growing at an accelerated pace over the past decade. The latest progress on developing automatic IQA methods that can predict subjective quality of visual signals is exhilarating. For example, a handful of objective IQA measures have been shown to significantly and consistently outperform the widely adopted mean squared error (MSE) and peak signal-to-noise-ratio (PSNR) in terms of correlations with subjective quality evaluations [1].