Image quality assessment plays an important role in various image processing applications. A great deal of etTort has been made in re cent years to develop objective image quality metrics that correlate with perceived quality measurement. Unfortunately, only limited success has been achieved. In this paper, we provide some insights on why image quality assessment is so difficult by pointing out the weaknesses of the error sensitivity based framework, which has been used by most image quality assessment approaches in the lit erature. Furthermore, we propose a new philosophy in designing im age quality metrics: The main function of the human eyes is to �tract structural i'!formation from the viewing field, and the hu man visual system is highly adapted for this purpose. Therefore, a measurement of structural distortion should be a good approxima tion of perceived image distortion. Based on the new philosophy, we implemented a simple but effective image quality indexing al gorithm, which is very promising as shown by our current results.
Image quality assessment is a difficult process which plays a major role in various processing applications REF .
Why is image quality assessment so difficult?
2002 IEEE International Conference on Acoustics, Speech, and Signal Processing
2002 IEEE International Conference on Acoustics, Speech, and Signal Processing
Computer Science