Abstract
The effect of noise on image quality is investigated using human evaluations of a set of images with a wide range of noise and blur levels. Quality is quantified in terms of the smallest contrast feature that can be reliably identified in a test pattern which can be equated to an effective visual resolution. It is found that the image starts to degrade as SNR falls below 50 and below 10 resolution becomes primarily determined by SNR and is insensitive to blur level. The visual information fidelity metric is shown to accurately model the human response.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
