Digital image processing - Download file di http://rumah-belajar.org

1. Visual Quality Assessment
T.L.R. Mengko

3. Bad vs Good Potato

4. Visual Quality Measurement
• Measurement of visual quality is of fundamental
importance to numerous image and video processing
applications.
• The goal of quality assessment (QA) to automatically
assess the quality of images or videos in a perceptually
consistent manner.
• Image QA algorithms generally interpret image quality as
fidelity or similarity with a ‘reference’ or ‘perfect’ image in
some perceptual space.
• Such ‘Full-Reference’ QA methods attempt to achieve
consistency in quality prediction by modeling salient
physiological and psycho-visual features of the human
visual system (HVS), or by signal fidelity measures.

5. Describing Existing Visual Resources

8. Some Parameters
• mean-squared-error 'MSE'
• peak signal-to-noise-ratio 'PSNR'
• structural similarity index 'SSIM'
• multi-scale SSIM index 'MSSIM'
• visual signal-to-noise ratio 'VSNR'
• visual information fidelity 'VIF'
• pixel-based VIF 'VIFP'
• universal quality index 'UQI'
• information fidelity criterion 'IFC'
• noise quality measure 'NQM'
• weighted signal-to-noise ratio 'WSNR'
• signal-to-noise ratio 'SNR'