The Implementation, in Matlab, of Three Digital Image Processing Algorithms to Evaluate the Change of Parameters of Two Consecutive Images

The assessment of quality of the image plays an important role in many processing applications developments. A great effort has been carried out in recent years in this field to develop and implement image quality metrics that correlate with measures of the quality expected. In fact, a great success this domain is not achieved. In this paper we have implemented three algorithms in Matlab that evaluate two consecutive images. These algorithms are: Mean Opinion Score (MOS), Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM).Currently, we have considered 50 pairs of consecutive images retrieved from a video with a difference of 1 ms, which will be subject of entry in these three algorithms developed in Matlab. After we enter these couples of images, three numbers will appear which define the level of changing the two images parameters. The results generated will be given through statistical conclusions of spline interpolation fitting. Finally, the limitations of this study concentrate on the development and improvement of these three algorithms in such a way that the evaluation must be done as correctly as possible in cases where the difference in pixels between the two images is larger