Sinopsis
Humans are highly visual creatures. Evolution has invested a large part of our neurological resources in visual perception. We are experts at grasping visual environments in a fraction of a second and rely on visual information for many of our day-to-day activities. It is not surprising that, as our world is becoming more digital every day, digital images and digital video are becoming ubiquitous.
In light of this development, optimizing the performance of digital imaging systems with respect to the capture, display, storage and transmission of visual information is one of the most important challenges in this domain. Video compression schemes should reduce the visibility of the introduced artifacts, watermarking schemes should hide information more effectively in images, printers should use the best half-toning patterns, and so on. In all these applications, the limitations of the human visual system (HVS) can be exploited to maximize the visual quality of the output. To do this, it is necessary to build computational models of the HVS and integrate them in tools for perceptual quality assessment
Content
- Vision
- Video Quality
- Models and Metrics
- Metric Evaluation
- Metric Extensions
- Closing Remarks
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