In this Keynote Address paper, we review early work on Image and Video Quality Assessment against the backdrop of
an interpretation of image perception as a visual communication problem. As a way of explaining our recent work on
Video Quality Assessment, we first describe our recent successful advances on QA algorithms for still images,
specifically, the Structural SIMilarity (SSIM) Index and the Visual Information Fidelity (VIF) Index. We then describe
our efforts towards extending these Image Quality Assessment frameworks to the much more complex problem of
Video Quality Assessment. We also discuss our current efforts towards the design and construction of a generic and
publicly-available Video Quality Assessment database.