In this work, we present a SSIM optimal JPEG 2000 rate allocation algorithm. However, our aim is less improving the visual performance of JPEG 2000, but more the study of the performance of the SSIM full reference metric by means beyond correlation measurements.Full reference image quality metrics assign a quality index to a pair of a reference and distorted image. The performance of a metric is then measured by the degree of correlation between the scores obtained from the metric and those from subjective tests. It is the aim of a rate allocation algorithm to minimize the distortion created by a lossy image compression scheme under a rate constraint.Noting this relation between objective function and performance evaluation allows us now to define an alternative approach to evaluate the usefulness of a candidate metric: we want to judge the quality of a metric by its ability to define an objective function for rate control purposes, and evaluate images compressed in this scheme subjectively. It turns out that deficiencies of image quality metrics become much easier visible --- even in the literal sense --- than under traditional correlation experiments.Our candidate metric in this work is the SSIM index proposed by Sheik and Bovik which is both simple enough to be implemented efficiently in rate control algorithms, but yet correlates better to visual quality than MSE; our candidate compression scheme is the highly flexible JPEG 2000 standard.