A New Quality Metric based on FFT Transform

The study of the human visual system (HVS) is very interesting to quantify the quality of an image or to predict perceived information. The contrast sensitivity function (CSF) is one of the main ways to incorporate the HVS properties in an imaging system. It characterizes its sensitivity to spatial and temporal frequencies. In this paper we are interested in establishing a metric with full reference to the image and video. We realize in our algorithm, the FFT transformation to apply the CSF function. Our method is applicable to any size of image and video sequence by increasing its size at powers of two. This increase is achieved by adding "mirror image". The experimental results show that our method keeps better the different frequency components. She is more efficient than the method of "zero padding" and returns results very close to those of the DFT transformation. General Terms Signal processing, image quality metric.