ACI: a bar chart index for non-linear visualization of data embedding and aggregation capacity in IoMT multi-source compression

Abstract

Visualization of numerical results in computer communications is very important such that some very small differences are sometimes crucial, distinguishable, and descriptive for comparison among some state-of-the-art techniques. For the issue of data quality evaluation and compression rates in internet of multimedia things, there are many metrics traditionally, for instance, peak signal-to-noise ratio (PSNR) is strongly able to describe non-sensitive (and relatively ambiguous) results of mean square error and since PSNR is normally between 10 and 100 for most of the lossy techniques, it can plotted with using any graphical/visualization tool. However, the results of compression rates for aggregation techniques may be a little complicated on which using a non-flexible mathematical operator like logarithm may have an unsuitable effect with ignoring the small differences while plotting the results. The aim behind this paper is to introduce a new metric entitled average capacity index (ACI), as a non-linear visualization approach/scaling mechanism, to be usable in evaluating capacity results of data hiding and aggregation algorithms based on bar charts. Some examples with synthetic and real data will show that the proposed metric outperforms the existing conventional tools in terms of statistical measures and visual presentation.