ABSTRACT
Evaluation methodologies provide a better understanding of the relationship between a technique and the image attributes. Metrics are used to evaluate the similarities between images. They may use different approaches depending on what needs to be achieved. If only objective values need to be compared statistics-based metrics are suitable. A number of image comparison metrics have been proposed in the literature that is based mostly on images statistics. This chapter shows the MATLAB code for the root mean square error (RMSE) calculation. It presents the MATLAB code for the computation of mean square error (MSE) between two images. Peak signal to noise ratio (PSNR) is another widely used metric, which takes into account the maximum value of the signal, and can be defined based on MSE. Metrics enable automation and the use of metrics can also be applied directly to methods, for example, to identify if further refinement for compression produces any noticeable differences.
