Score System The VCX score is a numeric indicator of mobile phones and products and is based on an objective assessment of equipment. It does not contain any visual assessment or other subjective factors. The only subjective component is the weighting, that is, the decision of which metric is more important for the overall performance compared to others. This weighting has been accurately determined by a group of experts and it is identical for every device, so the comparison between devices is fixed and not influenced by individual opinions. Bright light conditions [ISO 50 - f/1.8 - 1/50s] 80/100 Medium light conditions [ISO 200 - f/1.8 - 1/50s] 73/100 Low light conditions [ISO 320 - f/1.8 - 1/25s] 65/100 Flash light [ISO 160 - f/1.8 - 1/50s] 75/100 Zoom [ISO 80 - f/2.4 - 1/50s] 39/100 Response & performance - 82/100 The total score range is between 0 and 100 The range is designed in such a way that a value of 100 means that the device yields the best possible result in every metric that is achievable with today’s camera technology. It is therefore possible that in the future the value of 100 will be exceeded or that the range has to be modified. The score is the sum of the image quality score and the handling score. 12/100 The image quality score is generated from different test conditions. For each of the metrics used, a single score is calculated via bespoke algorithms/formulae developed specifically for VCX by VCX members, derived from use-case studies. The total score is a weighted sum of the individual scores. The weighting of the different aspects of the image quality is the result of a case study on how mobile phones are used as well as internal research. It correlates well with the outcome of other independent studies. The transformation of metrics into scores is performed under the definition of a theoretical worst and theoretical best value. The scaling is performed in different ways between the extreme points, depending on the metric itself. For some metrics, the correlation between “metric” and “influence in image quality” is linear, so the score is a linear function of the metric. This would be in the case of a simple “the higher the better” or “the lower the better” assumption. For others, this assumption is not true. Some metrics require a different approach to the one previously mentioned, because it would not reflect the perceived quality. Sharpening is a good example for this behaviour. No sharpening is not beneficial for the image quality, as an image would appear flat. At the same time, too much sharpening very quickly results in an artificial and unpleasant. So, there is a “sweet spot” below or above which leads to a reduction in the score. We regularly check the latest development in the camera industry and will update the test procedure and the score generation process as soon as we see that it does not reflect the improvements in camera performance or when new technologies need to be included in the procedure.