WNCG Seminar: Perceptual Quality Evaluation of Pan-sharpened and Super-resolved Images

The role of image quality assessment in tasks such as (i) pan sharpening (PS) (i.e. merging high-resolution panchromatic and lower resolution multispectral imagery to create a single high-resolution color image) and (ii) super-resolution (SR) has not been researched extensively from the natural scene statistics (NSS) perspective. For instance, even though there are several well-known measures that quantify the quality of PS and SR images, there has been little work done on analyzing the statistics of PS and SR images and associated distortions. In this talk, we will present opinion-aware (OA) and opinion-distortion-unaware (ODU) image quality analyzers whose quality prediction power exceeds that of other state-of-the-art PS and SR quality models in regards to correlation with human subjective judgments. These results confirm the relevance of NSS for improving non-reference quality evaluation of image enhancement procedures such as PS and SR.