How to generate perceptual mask for watermarking ?
Perceptual mask tells us the maximum change on can make to a pixel (in case of images/video), before the change becomes noticeable. It can also be defined the other way around like, the limit of change on could impart on the the pixel value while watermark insertion and still be invisible. Some authors call the functions which generate the scale of visibility due to watermark as Just Noticeable Difference (JND) or Noise Visibility Functions (NVF). JND uses standard deviation and thus makes the watermark appear very strong in the edges. Some models like watson metric, non-stationary Guassian model and PSNR quality metric can be found in checkmark benchmarking tool. More information about DVQ(Digital Video Quality) watson metric can be found at http://www.nasatech.com/Briefs/Apr01/ARC14236.html. You can futher find several others metric computations which measure image quality like S. Daly.
Perceptual mask tells us the maximum change on can make to a pixel (in case of images/video), before the change becomes noticeable. It can also be defined the other way around like, the limit of change on could impart on the the pixel value while watermark insertion and still be invisible. Some authors call the functions which generate the scale of visibility due to watermark as Just Noticeable Difference (JND) or Noise Visibility Functions (NVF). JND uses standard deviation and thus makes the watermark appear very strong in the edges. Some models like watson metric, non-stationary Guassian model and PSNR quality metric can be found in checkmark benchmarking tool. More information about DVQ(Digital Video Quality) watson metric can be found at http://www.nasatech.com/Briefs/Apr01/ARC14236.html. You can futher find several others metric computations which measure image quality like S. Daly. “The Visual Difference Predictor : An Algorithm for the Assessment of Visual Fidelity.” in Digital
