Shahin Shafei
The Human Visual System (HVS) is incredibly variable from one person to another and even under different conditions for the same person. Parameterizing allows for this -personalizationâ?? while maintaining the familiar property that, if a visually -fineâ?? image is added to another visually -fineâ?? image, the result should also be -fine.â?? we find that the separate operations generally work best when the parameter values are the same by insuring a visually pleasing result, this should help to improve image enhancement performance. Similar training methods have been introduced in the past and used for a number of applications. Further, we find that good results can be obtained without training the system for individual images, however by utilizing the training system on a specific problem one may have the best results.
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